https://www.spreaker.com/podcast/datascience-show-podcast--6817783
datascience.show

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.]]>enBusinessMirko Petershttps://d3wo5wojvuv7l.cloudfront.net/t_rss_itunes_square_1400/images.spreaker.com/original/dff6f3ae8770d2f2f67ca5abee033a7e.jpghttps://www.spreaker.com/podcast/datascience-show-podcast--6817783Sat, 25 Jul 2026 00:52:13 +0000Mirko PetersMirko Petersmirko.peters@datascience.showWelcome to The DataScience Show, hosted by Mirko Peters — your daily source for everything data! Every weekday, Mirko delivers fresh insights into the exciting world of data science, artificial intelligence (AI), machine learning (ML), big data, and...
datascience.show

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.]]>falsec2fe72a0-afaa-520d-a964-f864ae578374episodicSupport the podcast!https://www.spreaker.com/episode/from-proof-to-product-the-executive-playbook-for-ai-product-management--73159979
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>cd291bd5-cc95-44fe-8355-6a5e7d1df786Sat, 25 Jul 2026 00:36:35 +0000Mirko PetersMany enterprises stall at pilots because they treat machine learning as a project, not a product. This episode gives C-level leaders a practical playbook for building AI product management as a repeatable capability: a governance-backed lifecycle that...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>543false122fullhttps://www.spreaker.com/episode/causal-roi-an-executive-playbook-to-measure-real-business-impact-of-ai--73136158
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>7752f00b-7000-4a15-beb0-8e41c70f9b67Fri, 24 Jul 2026 00:39:31 +0000Mirko PetersMany AI initiatives report technical metrics but fail to prove business impact. This episode gives C-level leaders a practical, non-technical playbook for turning models into accountable investments by embedding causal measurement, controlled...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>429false121fullhttps://www.spreaker.com/episode/model-observability-for-executives-turning-alerts-into-business-confidence--73116528
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>4beae028-72d3-4871-a006-e5ed9d3d08e7Thu, 23 Jul 2026 00:37:10 +0000Mirko PetersExecutives routinely hear about model drift, data skew, and false positives, but struggle to understand which signals actually matter for the business. This episode walks senior leaders through a pragmatic, product-minded approach to model...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>474false120fullhttps://www.spreaker.com/episode/changing-behavior-a-c-level-playbook-to-embed-ai-into-everyday-decisions--73096274
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>0c27cf39-1012-47c1-ba39-f648c6d31083Wed, 22 Jul 2026 00:28:57 +0000Mirko PetersMany AI projects fail not for technical reasons but because organizations don’t change the decision architecture that surrounds models. This episode is a practical C-level monologue that lays out a playbook for embedding AI into everyday business...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>461false119fullhttps://www.spreaker.com/episode/internal-pricing-for-ai-how-chargebacks-and-product-pricing-turn-models-into-sustainable-business-units--73078023
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>37680f90-ce39-41b5-8369-17b8751241f4Tue, 21 Jul 2026 00:33:34 +0000Mirko PetersMany enterprise AI efforts stall not because models fail but because incentives, visibility, and funding are misaligned. This episode gives C-level leaders a pragmatic playbook for designing internal pricing and chargeback models that make AI costs...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>552false118fullhttps://www.spreaker.com/episode/ai-investment-portfolio-an-executive-playbook-to-prioritize-fund-and-de-risk-ai-initiatives--73061565
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>e919e8ec-64c9-4f8c-9357-153c05fc3ac9Mon, 20 Jul 2026 00:32:30 +0000Mirko PetersMost organizations run AI projects as isolated bets: promising pilots, scattered budgets, uneven governance, and inconsistent outcomes. This episode delivers a practical, exec-level playbook for treating AI initiatives as a coherent investment...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>454false117fullhttps://www.spreaker.com/episode/the-responsible-ai-executive-scorecard-kpis-that-turn-ethics-into-business-outcomes--73049516
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>f5616d1f-6bb1-408c-b93c-5e31a1307b51Sun, 19 Jul 2026 00:40:12 +0000Mirko PetersFor executives the language of ethics and governance often feels disconnected from balance sheets. This episode delivers a practical, executive-focused playbook for defining, measuring, and governing Responsible AI through a compact scorecard that...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>516false116fullhttps://www.spreaker.com/episode/scaling-human-in-the-loop-ai-executive-design-patterns-for-reliable-collaboration--73036235
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>c9c94667-df12-41a4-bbdf-aba2eb7f2a7fSat, 18 Jul 2026 00:24:46 +0000Mirko PetersEnterprises increasingly depend on systems where humans and automated models collaborate—fraud review queues, content moderation, clinical decision support, and assisted sales. This episode gives C-level leaders a pragmatic playbook for turning...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>484false115fullhttps://www.spreaker.com/episode/data-contracts-for-enterprise-ai-from-slas-to-trust--73020272
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d511e194-1a8a-4b36-9063-2ca5ad0aa669Fri, 17 Jul 2026 00:28:24 +0000Mirko PetersThis episode gives executives a practical, operational roadmap for data contracts: formal agreements that define ownership, quality SLAs, access policies, and observability for data products that power AI at scale. Mirko frames why data contracts are...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>495false114fullhttps://www.spreaker.com/episode/m-a-for-ai-the-executive-playbook-to-capture-data-ai-value-in-acquisitions--73004477
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d0526ad7-5fa9-474a-89e9-3fc73ecb1dfcThu, 16 Jul 2026 00:25:38 +0000Mirko PetersMergers and acquisitions are high-stakes moments where promised AI advantage either becomes strategic value or sinks into technical debt. This monologue episode equips C-level leaders with a pragmatic, repeatable playbook to evaluate target data and...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>779false113fullhttps://www.spreaker.com/episode/from-confidence-intervals-to-board-decisions-translating-model-uncertainty-into-executive-risk-narratives--72980429
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>f5338d41-9555-4b73-95af-092e649cead5Wed, 15 Jul 2026 00:28:39 +0000Mirko PetersMany boards hear model outputs as precise directives when in reality every prediction carries uncertainty. This episode gives C‑level leaders a practical playbook for translating model uncertainty into tight risk narratives, decision thresholds, and...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>622false106fullhttps://www.spreaker.com/episode/when-to-retire-a-model-an-executive-playbook-for-model-sunset-lifecycle-optimization--72980427
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>1bcf74fb-bfa7-425b-96a9-aad7793d6296Wed, 15 Jul 2026 00:28:39 +0000Mirko PetersMany organizations focus on deploying models, but few have an executive-level strategy for when and how to retire, consolidate, or re-scope models. This episode delivers a compact, operational playbook for C-level leaders and senior data executives to...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>650false105fullhttps://www.spreaker.com/episode/causal-confidence-turning-correlation-into-executive-decisions--72980424
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>c0363c5f-9053-41bd-a237-c79516d4a67fWed, 15 Jul 2026 00:28:39 +0000Mirko PetersMany executive teams still treat predictive signals as causal levers—leading to costly, inconsistent interventions. This episode gives senior leaders a practical, non-technical playbook for making causal thinking operational across the enterprise. We...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>597false111fullhttps://www.spreaker.com/episode/ai-economics-an-executive-playbook-for-budgeting-measuring-and-optimizing-ai-spend--72980422
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>8812a8b9-774b-402c-9479-f6fd06b1ab3aWed, 15 Jul 2026 00:28:39 +0000Mirko PetersEnterprises routinely underestimate the ongoing costs of production AI: cloud inference, retraining, data pipelines, model ops, and organizational overhead. This episode gives C‑level leaders and senior data executives a compact, actionable playbook...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>617false109fullhttps://www.spreaker.com/episode/from-proofs-to-production-the-executive-playbook-for-model-ownership--72980415
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>2b478c41-5a5a-4016-8082-05d3c5e649eeWed, 15 Jul 2026 00:28:39 +0000Mirko PetersMany organizations spin up impressive prototypes but struggle to capture sustained value from machine learning. In this 23-minute episode Mirko lays out a compact, actionable playbook for executives to close the gap between experimentation and...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>583false104fullhttps://www.spreaker.com/episode/retire-replace-reuse-an-executive-playbook-for-model-decommissioning-and-ml-technical-debt--72980410
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>77bf5b8e-3675-4790-a59c-b8303e333d02Wed, 15 Jul 2026 00:28:39 +0000Mirko PetersEnterprises rarely plan for the end of an ML system. This episode gives C-level leaders a pragmatic playbook for the overlooked final stage of the model lifecycle: decommissioning and managing accumulated technical debt. Mirko unpacks how to recognize...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>585false108fullhttps://www.spreaker.com/episode/productize-to-scale-the-executive-playbook-for-data-products--72980409
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>dd032ede-cfeb-4fd7-8634-105ab24cec3fWed, 15 Jul 2026 00:28:39 +0000Mirko PetersMost organizations treat analytics as projects; product-minded leaders treat them as repeatable products. This episode gives C-level listeners a practical playbook for converting insights, models, and data services into reliable data products with...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>528false112fullhttps://www.spreaker.com/episode/from-metrics-to-money-building-an-outcome-first-ai-metrics-program-for-leaders--72980407
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>9fcc6c3a-9702-48fa-81ad-4cb73b4c6d1eWed, 15 Jul 2026 00:28:39 +0000Mirko PetersThis episode gives C-level leaders and senior data practitioners a practical, executive-focused blueprint for translating data science outputs into measurable business outcomes. Rather than talking about models or tools, the monologue walks through...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>591false107fullhttps://www.spreaker.com/episode/metric-engineering-translating-business-kpis-into-model-level-objectives--72980397
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>9e91b9a8-0681-449b-a545-baf6aa8c8e06Wed, 15 Jul 2026 00:28:39 +0000Mirko PetersLeaders often ask why high-performing models don’t translate to measurable business outcomes. This episode presents a focused playbook for metric engineering—the discipline of mapping business KPIs to model objectives, evaluation metrics, and...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>550false110fullhttps://www.spreaker.com/episode/managing-third-party-ai-risk-a-c-level-playbook-for-vendors-models-and-data-supply-chains--72943657
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>cfad06fc-60f1-4ef8-9238-07ccaf644650Mon, 13 Jul 2026 01:22:23 +0000Mirko PetersEnterprises increasingly deliver value through models and data they did not build. This monologue gives C-level leaders a pragmatic playbook to turn third-party AI suppliers from uncontrolled risk into governed strategic partners. I cover how to...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>437false103fullhttps://www.spreaker.com/episode/decision-intelligence-for-executives-turning-ai-signals-into-strategic-decisions--72934281
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>6e685e62-4315-4a0d-bace-c597017f20cfSun, 12 Jul 2026 00:22:37 +0000Mirko PetersExecutives often treat AI as a technical capability rather than a decisioning system. This episode reframes AI as Decision Intelligence — a structured approach that connects models, human judgment, incentives, and operational processes so predictive...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>495false102fullhttps://www.spreaker.com/episode/synthetic-data-strategy-an-executive-playbook-for-privacy-first-high-utility-ai--72923191
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d1f4afe4-2535-4480-9ccb-480c2424d878Sat, 11 Jul 2026 00:32:05 +0000Mirko PetersMany executives hear about synthetic data as a shortcut to more training data and tighter privacy, but the real challenge is turning it into predictable, auditable business value. This episode gives senior leaders a practical playbook: when synthetic...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>565false101fullhttps://www.spreaker.com/episode/model-retirement-an-executive-playbook-for-responsible-end-of-life-in-enterprise-ai--72902462
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>45b6d5cd-3e9b-4a2e-97ce-c72e6498abbfFri, 10 Jul 2026 00:38:15 +0000Mirko PetersMost enterprises obsess about model build and deployment—far fewer plan for model retirement. This episode gives C-level leaders a practical, executive-focused playbook to treat model end-of-life as a strategic discipline. Mirko walks listeners...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>427false100fullhttps://www.spreaker.com/episode/operational-resilience-for-ai-building-incident-ready-ml-systems--72877717
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>4b60d628-bdb1-474d-847c-ac80d8cf0195Thu, 09 Jul 2026 00:32:04 +0000Mirko PetersEnterprises routinely measure model accuracy and launch pilots — but few design for the inevitable: incidents, data drift, and unexpected downstream impact. This episode gives C-level leaders and senior practitioners a pragmatic, execution-focused...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>526false99fullhttps://www.spreaker.com/episode/governed-experimentation-an-executive-playbook-for-safe-high-tempo-ml-innovation--72861081
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d1199693-dbe3-45c3-aded-8fd9bbfdd28cWed, 08 Jul 2026 00:30:51 +0000Mirko PetersToo many organizations prize speed in machine learning but lack the governance to protect operations and value. This episode is a C‑level playbook on governed experimentation: how executives create structures, guardrails, and incentives that let teams...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>511false98fullhttps://www.spreaker.com/episode/data-mesh-for-executives-organizing-people-incentives-and-platforms-to-deliver-data-products--72846618
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>642aec72-4cc7-4eeb-bbf4-cc2d970eee57Tue, 07 Jul 2026 00:51:27 +0000Mirko PetersThis episode gives C-level leaders and senior data executives a compact, actionable playbook for adopting a data-mesh approach without mistaking architecture for transformation. Mirko walks through the non-technical decisions that determine success:...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>437false97fullhttps://www.spreaker.com/episode/ai-finops-the-c-level-playbook-for-funding-charging-and-optimizing-enterprise-ai--72833463
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>77195196-38a7-4744-9410-fafa30e05a47Mon, 06 Jul 2026 00:26:41 +0000Mirko PetersMany enterprises invest heavily in AI without a consistent approach to funding, cost attribution, or ongoing optimization. This episode gives C-level leaders a pragmatic playbook—AI FinOps—for aligning finance, engineering, and product teams around...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>528false96fullhttps://www.spreaker.com/episode/shadow-ai-at-scale-an-executive-playbook-to-discover-assess-and-integrate-unsanctioned-ai--72823307
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>73471d05-dd4c-487e-adc4-a05bf388115bSun, 05 Jul 2026 00:25:22 +0000Mirko PetersMany enterprises now face a proliferation of employee-led AI: external LLMs, purpose-built scripts, and small automations that operate outside formal governance. This episode gives C‑level leaders a practical, non-technical playbook to discover shadow...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>487false95fullhttps://www.spreaker.com/episode/ai-investment-portfolio-a-c-level-playbook-to-prioritize-stage-gate-and-measure-value--72812540
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>1eb0a17e-d289-4adc-969d-e2d0b8c53585Sat, 04 Jul 2026 00:26:08 +0000Mirko PetersMany organizations fund AI as a set of isolated projects rather than as a strategic investment portfolio. This episode gives C‑level leaders a step‑by‑step playbook to treat AI like a product portfolio: prioritize by expected economic value and...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>540false94fullhttps://www.spreaker.com/episode/productizing-enterprise-ai-a-c-level-playbook-for-ai-product-management--72796894
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>83799130-1eb6-481f-9f24-d37dbdbc5d9bFri, 03 Jul 2026 00:25:05 +0000Mirko PetersMany enterprises treat AI as experiments rather than products. This episode gives C-level leaders a pragmatic playbook for productizing AI—installing roles, metrics, roadmaps, and processes that convert models into repeatable, revenue-driving...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>556false93fullhttps://www.spreaker.com/episode/buying-ai-wisely-an-executive-playbook-for-procurement-contracts-and-vendor-risk--72781090
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>7928d157-9ed7-4a0b-8fa3-a6f6cce3f736Thu, 02 Jul 2026 00:26:38 +0000Mirko PetersMany executives treat AI vendors like technology purchases instead of strategic, operational partnerships—resulting in hidden costs, brittle integrations, unclear accountability, and regulatory blind spots. This episode offers a practical,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>454false92fullhttps://www.spreaker.com/episode/decisionops-an-executive-playbook-to-turn-models-into-repeatable-business-decisions--72764139
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>f8eb0258-c201-48cc-8515-34103e757b55Wed, 01 Jul 2026 00:23:29 +0000Mirko PetersMany organizations build models but fail to convert predictions into repeatable, measurable decisions. This episode presents a pragmatic DecisionOps playbook for executives: how to design decision contracts, embed model outputs into business...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>508false91fullhttps://www.spreaker.com/episode/human-in-the-loop-ai-an-executive-playbook-to-scale-expert-ai-collaboration--72749704
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>0c4c19d9-c73c-4c9c-a67d-d746a7978994Tue, 30 Jun 2026 00:23:49 +0000Mirko PetersThis episode equips C-level leaders and senior data practitioners with a practical playbook for operationalizing human-in-the-loop (HITL) AI across the enterprise. Mirko walks listeners through why deliberate HITL design is not a temporary patch but a...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>448false90fullhttps://www.spreaker.com/episode/data-contracts-and-federated-data-ownership-an-executive-playbook-to-build-trust-and-scale-decision-ready-data--72733494
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>bd44d684-7c16-4432-9ffb-b9da8d596f53Mon, 29 Jun 2026 00:22:50 +0000Mirko PetersEnterprises struggle not from lack of data but from friction: unclear ownership, brittle integrations, and recurring trust issues that stall AI initiatives. This episode is a strategic, executive-focused monologue that translates the mechanics of data...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>484false89fullhttps://www.spreaker.com/episode/business-driven-model-observability-linking-model-signals-to-roi--72723969
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b1bdaeaf-efc2-4159-a250-8cb218e74176Sun, 28 Jun 2026 01:22:37 +0000Mirko PetersMany organizations instrument models for accuracy and latency but fail to connect those signals to business impact. This episode gives C-level leaders and senior data practitioners a practical, repeatable framework to align model observability with...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>479false88fullhttps://www.spreaker.com/episode/governing-continuous-learning-ai-an-executive-playbook-for-safe-reliable-online-models--72709414
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b0d4757a-e8a5-4def-b5b0-b009e126704dSat, 27 Jun 2026 00:23:15 +0000Mirko PetersMany enterprises are moving from static, periodically retrained models to continuous-learning systems that update in production. This episode gives C-level leaders a practical playbook for governing adaptive models: defining safety guardrails,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>588false87fullhttps://www.spreaker.com/episode/ai-incident-response-an-executive-playbook-for-preparing-responding-and-learning-from-ai-failures--72695798
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b29558b7-057a-4821-bad9-fa238b90b573Fri, 26 Jun 2026 00:22:55 +0000Mirko PetersEnterprises treat AI like software they can ship and forget. The reality: AI systems fail in new, systemic ways—silent performance drift, unfair outcomes, data poisoning, or automation cascades that magnify business risk. This episode gives C-level...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>572false86fullhttps://www.spreaker.com/episode/feature-platforms-as-strategic-assets-an-executive-playbook-for-building-and-governing-reusable-features--72685337
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>c37e5066-0989-4346-91ec-ebd40848aa14Thu, 25 Jun 2026 00:00:00 +0000Mirko PetersThis episode reframes feature engineering from a tactical pipeline task into a strategic, executive-level capability: the feature platform. Mirko delivers a focused monologue that explains why reusable, discoverable, and governed features are the...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>401false85fullhttps://www.spreaker.com/episode/synthetic-data-strategy-for-enterprise-ai-an-executive-playbook-to-unlock-privacy-safe-training-data--72624272
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>95b6313b-9590-4b3b-a8b4-239167b8a2b0Mon, 22 Jun 2026 00:23:05 +0000Mirko PetersMany enterprises see synthetic data as a promising shortcut to more labeled data and safer sharing, but few have turned it into a repeatable, measurable capability. This episode gives C-level leaders and senior data executives a practical playbook for...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>554false84fullhttps://www.spreaker.com/episode/m-a-for-ai-an-executive-playbook-for-due-diligence-value-capture-and-integration--72615351
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>df310071-dbcf-4872-bec6-b2a2f9732ad7Sun, 21 Jun 2026 00:23:40 +0000Mirko PetersAcquiring AI teams, models, and data is increasingly a strategic shortcut to capability—but M&A for AI requires its own executive playbook. This episode walks senior leaders through a pragmatic sequence: what to evaluate in technology, data,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>468false83fullhttps://www.spreaker.com/episode/productizing-data-an-executive-playbook-to-turn-models-into-revenue-generating-data-products--72606405
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>22d6b3b1-ec95-4486-a804-219930e26fbcSat, 20 Jun 2026 00:24:01 +0000Mirko PetersMany organizations struggle to convert successful ML prototypes into scalable, revenue-producing data products. This episode gives senior leaders a practical playbook for closing that gap: how to define a product mindset for data, choose monetization...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>432false82fullhttps://www.spreaker.com/episode/managing-ml-technical-debt-an-executive-playbook-to-measure-prioritize-and-retire-risk--72591316
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>bc8b56d8-0c62-4893-9a40-39de85b8ad45Fri, 19 Jun 2026 00:24:12 +0000Mirko PetersTechnical debt in machine learning is an invisible tax on performance, speed and trust that prevents organizations from converting experiments into sustained value. This episode gives C-level leaders and senior data practitioners a concrete playbook:...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>501false81fullhttps://www.spreaker.com/episode/human-in-the-loop-ai-an-executive-playbook-to-design-scale-and-govern-hybrid-decision-systems--72571510
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>85431267-dfe9-4af7-a12e-e42020ace9eeThu, 18 Jun 2026 00:23:34 +0000Mirko PetersThis episode delivers a practical C-level playbook for operationalizing human-in-the-loop (HITL) AI: systems where automated models and human judgment work together to make decisions. Mirko walks listeners through where HITL is the right design...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>582false80fullhttps://www.spreaker.com/episode/data-observability-as-executive-strategy-turning-telemetry-into-trust-and-faster-value--72557412
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>5defcea5-c797-43e1-a48b-4a7fa2bef9d0Wed, 17 Jun 2026 00:24:25 +0000Mirko PetersData observability is more than a monitoring toolset—it's an executive strategy that converts telemetry into trust, prioritization, and measurable business value. In this focused monologue Mirko presents a pragmatic playbook for C-level leaders and...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>588false79fullhttps://www.spreaker.com/episode/data-contracts-as-an-executive-lever-aligning-trust-ownership-and-value-in-the-data-supply-chain--72542544
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>7f71c299-99fe-4379-be5f-aa4f27af769bTue, 16 Jun 2026 00:23:44 +0000Mirko PetersExecutives know that unreliable data pipelines, ambiguous ownership, and informal SLAs are the invisible tax on enterprise AI. In this monologue Mirko lays out a C-level playbook for using formalized data contracts—clear schemas, SLAs, access...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>545false78fullhttps://www.spreaker.com/episode/decision-quality-a-c-level-playbook-for-measuring-and-governing-ai-driven-decisions--72527628
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>6c1e37a7-25aa-48d9-8a47-55c6a01be051Mon, 15 Jun 2026 00:23:33 +0000Mirko PetersExecutives often judge AI by model metrics—accuracy, AUC, latency—while the true question is whether AI improves decisions that matter to the business. In this 23-minute monologue Mirko presents a pragmatic C-level playbook for decision quality:...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>532false77fullhttps://www.spreaker.com/episode/operational-resilience-for-enterprise-ml-ensuring-continuity-when-models-fail--72516743
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>0f74e550-7254-4382-8dfa-84591289e153Sun, 14 Jun 2026 00:22:43 +0000Mirko PetersEnterprises treat models as value generators—but value stops the moment a model degrades, data pipelines break, or an unexpected event triggers poor decisions. This episode gives C-level leaders and senior practitioners a practical, operational...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>589false76fullhttps://www.spreaker.com/episode/feature-stores-as-strategic-infrastructure-a-c-level-playbook-for-governance-scale-and-roi--72507199
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>05e50f45-8b38-495b-a99d-f041ec58585dSat, 13 Jun 2026 00:23:36 +0000Mirko PetersFeature stores are often described as a technical layer for consistency and reuse—but for leaders they must become a strategic control point that unlocks reliable, auditable ML at scale. In this focused monologue Mirko translates the engineering...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>516false75fullhttps://www.spreaker.com/episode/ai-finops-for-leaders-a-c-level-playbook-to-manage-cost-incentives-and-value--72490676
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d893ba0c-1723-4c05-ab52-ffe13d4f45b1Fri, 12 Jun 2026 00:23:18 +0000Mirko PetersAI projects often fail to show repeatable returns because leaders treat compute, data, and model lifecycle costs as invisible overhead. This episode gives C-level leaders a compact, actionable playbook to bring financial rigor to AI: how to measure...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>510false74fullhttps://www.spreaker.com/episode/causalization-an-executive-playbook-to-turn-causal-inference-into-reliable-business-decisions--72468990
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>c9755a15-caa3-4e54-ba26-f688150259ddThu, 11 Jun 2026 00:23:21 +0000Mirko PetersExecutives know correlation-driven models can mislead decisions. This episode reframes how leaders move beyond predictive analytics to build causal decision systems that create measurable business impact. Mirko delivers a focused 23-minute executive...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>583false73fullhttps://www.spreaker.com/episode/model-portfolio-management-a-c-level-playbook-for-balancing-risk-roi-and-innovation--72446573
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>f1c672eb-0fa5-4e4a-9518-cb52344ffbeaWed, 10 Jun 2026 00:23:37 +0000Mirko PetersExecutives increasingly oversee dozens of production models across markets, products, and use cases. This episode gives C-level leaders a pragmatic playbook for managing AI as a portfolio: how to measure marginal value, balance short-term ROI against...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>537false72fullhttps://www.spreaker.com/episode/sustainable-ai-a-c-level-playbook-for-measuring-and-reducing-your-ai-carbon-footprint--72427952
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>c005379d-c0d2-4db2-a825-8abfbbe9854eTue, 09 Jun 2026 00:24:04 +0000Mirko PetersThis episode gives C-level leaders and senior data executives a pragmatic playbook for integrating sustainability into enterprise AI strategy. Rather than high-level rhetoric, it lays out measurable metrics (kWh, CO2e per inference/training,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>608false71fullhttps://www.spreaker.com/episode/ai-in-m-a-a-c-level-playbook-for-evaluating-integrating-and-realizing-value-from-ai-assets--72408900
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>74b6b73f-21ee-4319-8d7a-6d936f7d047dMon, 08 Jun 2026 00:23:45 +0000Mirko PetersThis episode gives C-level leaders a practical playbook for evaluating AI assets during mergers and acquisitions and for turning acquired machine learning, analytics, and data capabilities into measurable business outcomes. Mirko walks listeners...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>500false70fullhttps://www.spreaker.com/episode/from-experiment-to-investment-a-c-level-playbook-for-ai-economics--72395263
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b07d1ff7-5dfb-4a1e-821a-353fcf0119b1Sun, 07 Jun 2026 00:25:26 +0000Mirko PetersIn this episode Mirko presents a finance-forward playbook for turning AI pilots into repeatable, funded business initiatives. Framed around the perspective of a senior CDO/Head of AI at a large enterprise, the monologue walks through building a...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>519false69fullhttps://www.spreaker.com/episode/end-of-life-for-ml-a-c-level-playbook-for-retiring-replacing-and-decommissioning-models--72378368
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>ff6dc341-05a5-4e88-9c6d-96b70c22d953Sat, 06 Jun 2026 00:24:12 +0000Mirko PetersEnterprises often obsess over building models but under-invest in retiring them. This episode gives C-level leaders a clear playbook for knowing when to retire, replace, or decommission machine learning systems so they stop being liabilities and start...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>630false68fullhttps://www.spreaker.com/episode/synthetic-data-as-an-enterprise-strategy-a-practical-playbook-for-leaders--72356219
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>3cc04643-8632-47fb-98ac-b1d6ca5ee52cFri, 05 Jun 2026 00:22:53 +0000Mirko PetersThis monologue walks C-level and senior data leaders through a pragmatic playbook for adopting synthetic data across the enterprise. Rather than technical curiosities or vendor hype, the episode reframes synthetic data as a strategic instrument for...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>564false67fullhttps://www.spreaker.com/episode/data-contracts-as-executive-controls-a-c-level-playbook-for-trustworthy-data--72333399
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>882bcd6c-920e-4e24-a42e-4620baa51164Thu, 04 Jun 2026 00:23:03 +0000Mirko PetersExecutives often treat data quality and pipelines as an engineering nuisance. This episode reframes data contracts as strategic business controls that align product, analytics, and engineering around measurable SLAs. Mirko delivers a practical,...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>516false66fullhttps://www.spreaker.com/episode/observability-as-strategic-control-an-executive-playbook-for-data-model-monitoring--72309253
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>bda1101c-6489-4deb-8f70-ca63046a6348Wed, 03 Jun 2026 00:25:03 +0000Mirko PetersMany organizations treat observability as an engineering checkbox: dashboards, alerts, and occasional firefighting. This episode reframes observability as an executive-level control mechanism that links system telemetry to business outcomes,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>580false65fullhttps://www.spreaker.com/episode/audit-ready-ai-decision-platforms-an-executive-playbook-for-traceable-compliant-decisions--72286786
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>a62fb214-ed29-4d32-bf19-c531a7220828Tue, 02 Jun 2026 00:23:30 +0000Mirko PetersC-level leaders increasingly trust AI to make high-stakes decisions—from credit approvals to supply-chain exceptions and pricing overrides. This episode is a focused executive monologue that translates governance, engineering, and product trade-offs...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>549false64fullhttps://www.spreaker.com/episode/pricing-intelligence-executive-playbook-for-building-responsible-revenue-first-ml-systems--72268182
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>7dc2d6d6-a4b1-4ef4-8d3e-e58ce0c2a03aMon, 01 Jun 2026 00:24:36 +0000Mirko PetersPricing is where data science meets the P&L. This episode gives C-level leaders and senior data practitioners a practical playbook for turning pricing strategy into reliable, measurable machine learning services. I unpack the end-to-end decisions...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>572false63fullhttps://www.spreaker.com/episode/governing-continual-learning-an-executive-playbook-for-safe-sustainable-online-models--72256319
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>07ee41cd-39f3-4742-ad3b-f68d870cd801Sun, 31 May 2026 00:23:40 +0000Mirko PetersContinual learning and online model updates promise adaptive, personalized, and continually improving AI—but they also introduce novel operational, ethical, and regulatory risks that executives must manage. In this monologue tailored for C-level...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>577false62fullhttps://www.spreaker.com/episode/from-insight-to-action-a-c-level-playbook-for-building-enterprise-data-literacy--72217094
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>cc3da139-7bda-4590-a09e-c013dc8543b7Fri, 29 May 2026 00:25:35 +0000Mirko PetersFor C-level leaders and senior data professionals, technical models are only as valuable as the organization’s ability to use them. This episode unpacks a practical playbook for building enterprise data literacy—moving beyond one-off workshops to...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>558false61fullhttps://www.spreaker.com/episode/industrial-ai-in-production-an-executive-playbook-for-turning-sensor-data-into-reliable-business-services--72196492
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>171ff718-5b68-44c8-a12f-eb6832fc70c8Thu, 28 May 2026 00:23:56 +0000Mirko PetersIndustrial AI has unique constraints: distributed sensors, edge compute, safety regulations, long feedback loops, and hard ROI gates. This episode gives C-level leaders a compact, pragmatic playbook for turning industrial data and models into...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>596false60fullhttps://www.spreaker.com/episode/ai-integration-in-m-a-a-c-level-playbook-for-merging-data-models-and-teams--72177632
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>1e4bf7ef-32b0-4851-ae15-201b627bf038Wed, 27 May 2026 00:24:23 +0000Mirko PetersMergers and acquisitions routinely destroy or unlock value based on how data, models, and analytics teams are integrated. This episode gives C-level leaders a concise, operational playbook for the most critical—and often overlooked—parts of M&A:...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>511false59fullhttps://www.spreaker.com/episode/cost-aware-ml-quantifying-the-true-cost-per-prediction-and-aligning-models-to-business-roi--72161026
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>01a4fb98-0769-4d52-afc7-fec4b3792116Tue, 26 May 2026 00:25:58 +0000Mirko PetersExecutives often treat ML performance as a technical KPI rather than an economic one. This episode gives C-level leaders and senior data practitioners a pragmatic framework to quantify the full cost of a model decision—compute, latency, data...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>575false58fullhttps://www.spreaker.com/episode/model-end-of-life-an-executive-playbook-for-decommissioning-migration-and-risk-retirement--72147946
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b7e57542-1ae0-44a0-ada0-7c756e840b0eMon, 25 May 2026 00:27:39 +0000Mirko PetersEnterprises invest heavily to build, deploy, and maintain models—yet too few treat model retirement as a deliberate capability. This episode gives C-level leaders a practical playbook for when and how to decommission models, migrate capabilities, or...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>584false57fullhttps://www.spreaker.com/episode/data-contracts-as-organizational-glue-building-trust-between-data-producers-and-consumers--72135565
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>afaa2dbd-25a9-40c6-8946-c6f72e4f0656Sun, 24 May 2026 00:24:20 +0000Mirko PetersEnterprises routinely stall when the handoff between data producers and consumers is informal, slow, or mistrusted. This episode reframes data contracts as a strategic operating lever—an organizational capability that formalizes expectations, encodes...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>613false56fullhttps://www.spreaker.com/episode/model-observability-for-execs-turning-observability-into-business-controls--72123006
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d8fdbade-959b-43b1-b9df-9ec3d73365a3Sat, 23 May 2026 00:24:28 +0000Mirko PetersMost enterprises can build models, but few have turned model observability into a strategic control plane. This episode gives C-level leaders a practical blueprint for treating model observability as a business capability that enforces reliability,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>618false55fullhttps://www.spreaker.com/episode/insuring-ai-enterprise-strategies-for-liability-risk-transfer-and-governance--72118283
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>97719d13-02d6-4c16-ab41-8c870b108c41Fri, 22 May 2026 00:00:00 +0000Mirko PetersMany organizations treat insurance and legal frameworks as afterthoughts while deploying AI systems; that gap creates real financial and operational exposure. This episode presents a practical playbook for C-level leaders to treat AI liability as a...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>633false54fullhttps://www.spreaker.com/episode/ai-investment-portfolio-a-c-level-playbook-to-prioritize-and-fund-ai-initiatives--71844848
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>45a0b64c-7474-456e-9e32-43e437b86bdfMon, 04 May 2026 00:24:56 +0000Mirko PetersExecutives face a steady stream of AI proposals but rarely a disciplined method to prioritize, fund, and scale the ones that produce measurable business value. This episode introduces a pragmatic AI investment portfolio framework for C-level leaders:...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>546false53fullhttps://www.spreaker.com/episode/building-the-ai-runway-executive-capacity-planning-to-sustain-ai-at-scale--71833616
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>22d86e4b-d992-4b6d-bad7-4c8d31bb25f6Sun, 03 May 2026 00:55:28 +0000Mirko PetersMany AI initiatives stall not because the models are weak but because organizations run out of runway: data availability, compute, talent, or governance capacity. This episode gives C-level leaders a concise, operational framework to build a...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>628false52fullhttps://www.spreaker.com/episode/data-contracts-and-slo-driven-data-products-an-executive-playbook-to-treat-data-as-a-measurable-service--71822898
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>ae9af7af-be01-41dd-bd81-77e63be93622Sat, 02 May 2026 00:23:17 +0000Mirko PetersMany organizations struggle not for lack of models but for a lack of predictable, trustworthy data. This episode gives C-level leaders a practical playbook for treating data as a product governed by lightweight contracts, service-level objectives...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>621false51fullhttps://www.spreaker.com/episode/from-pilot-to-product-a-c-level-playbook-for-packaging-and-selling-enterprise-ai--71800319
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b0363b6d-b3f1-4d8f-a19a-7e1a93c8adf5Fri, 01 May 2026 00:23:33 +0000Mirko PetersMany AI initiatives stall at pilot or PoC because leaders treat models as technical artefacts instead of products. This episode gives C-level leaders a concrete playbook for productizing AI in enterprises: how to define the customer value proposition,...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>600false50fullhttps://www.spreaker.com/episode/when-models-break-an-executive-playbook-for-ai-incident-response--71661822
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>ebe759a6-c811-4a1d-9b71-aa9fefda8aa3Mon, 27 Apr 2026 00:22:51 +0000Mirko PetersIn this episode Mirko presents a concise, executive-focused playbook for responding when production AI systems fail, behave unpredictably, or cause downstream harm. Framed as a business continuity and governance problem rather than a pure engineering...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>586false49fullhttps://www.spreaker.com/episode/features-as-products-an-executive-playbook-for-strategic-feature-platforms--71645180
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>2b3116b3-0437-4686-a2ac-cc8a40f635eaSun, 26 Apr 2026 00:24:03 +0000Mirko PetersEnterprises investing in machine learning often overlook a single leverage point that separates pilots from production: features. This episode reframes features as products—discoverable, versioned, governed, and measured assets that executives must...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>628false48fullhttps://www.spreaker.com/episode/human-in-the-loop-at-enterprise-scale-building-decision-pipelines-executives-can-trust--71576006
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>b8cacd46-f423-4b9b-a46c-31eeabb23a9cThu, 23 Apr 2026 00:24:56 +0000Mirko PetersMany organizations treat AI as a drop-in automation rather than a decision partner. This episode gives C-level leaders a practical, strategic playbook for designing human-in-the-loop (HITL) pipelines that balance speed, accuracy, auditability, and...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>631false47fullhttps://www.spreaker.com/episode/shadow-ai-an-executive-playbook-to-discover-manage-and-harness-unofficial-ai-use--71537778
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>16b9099f-06ed-419e-a9fd-4be1561447ddWed, 22 Apr 2026 00:23:25 +0000Mirko PetersMany enterprises face a parallel AI economy: employees using external models, browser plugins, automation scripts, and SaaS features outside IT’s visibility. This episode gives C-level leaders a practical, strategic monologue on treating 'Shadow AI'...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>502false46fullhttps://www.spreaker.com/episode/economics-first-ml-a-c-suite-playbook-for-cost-aware-models-that-protect-margin--71506710
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>5fbfd6df-244e-4955-a03c-76fbeec20e66Tue, 21 Apr 2026 00:23:37 +0000Mirko PetersMany AI projects optimize predictive metrics but leave out the single largest lever for executives: the true economic consequences of model decisions. This episode is a decision-first monologue for C-level leaders and senior data practitioners that...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>697false45fullhttps://www.spreaker.com/episode/feature-as-product-a-c-suite-playbook-for-reusable-ml-assets--71446012
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>282a0bfe-e415-4816-a38c-ad4c48fbc4adSun, 19 Apr 2026 00:24:11 +0000Mirko PetersEnterprises routinely waste time and budget reengineering the same features across teams, leaving ML delivery slow, costly, and non-repeatable. This episode gives C-level leaders and senior data executives a concrete playbook to treat features as...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>542false44fullhttps://www.spreaker.com/episode/ml-chaos-playbook-a-c-suite-guide-to-testing-observability-and-recovery--71354838
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>89c7e4cb-c46f-426e-bbea-dc7eae90aaa8Thu, 16 Apr 2026 00:23:00 +0000Mirko PetersMany enterprise AI failures trace to untested assumptions at the intersection of models, data flows, and product behaviour. In this 23-minute, decision-first monologue Mirko synthesizes lessons from senior CDOs and ML leaders into a compact, fundable...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>695false43fullhttps://www.spreaker.com/episode/data-contracts-as-a-funded-service-a-board-ready-sla-template-and-90-day-pilot-for-reliable-data--71302402
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d927467f-50f8-41e2-b3e5-5efa5fbedb9eTue, 14 Apr 2026 00:27:17 +0000Mirko PetersEnterprises repeatedly lose time and value to brittle data handoffs: unknown ownership, unpredictable quality, and project delays. This monologue gives executives a decision‑first playbook to institutionalize 'Data Contracts as a Service.' Mirko lays...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>656false42fullhttps://www.spreaker.com/episode/synthetic-data-governance-an-executive-playbook-to-certify-procure-trust-synthetic-training-data--71265914
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>d5a72595-81ec-49e3-b950-f5346cd1982fSun, 12 Apr 2026 00:24:15 +0000Mirko PetersSynthetic data is rapidly becoming a core input for training, testing, and privacy-preserving sharing—but it brings unique governance, provenance, and legal trade-offs that boards must fund and control. This non‑technical, executive‑grade monologue...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>579false41fullhttps://www.spreaker.com/episode/uncertainty-accounting-a-c-suite-playbook-to-measure-budget-hedge-model-overconfidence--71199321
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>60f352c2-4098-442e-8b22-1a8c55e84425Thu, 09 Apr 2026 00:25:42 +0000Mirko PetersModels don't just make mistakes—they can be confidently wrong. This non‑technical, executive‑grade monologue shows leaders how to turn abstract uncertainty into board‑read controls: a taxonomy of uncertainty (aleatoric, epistemic, distributional...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>569false40fullhttps://www.spreaker.com/episode/purchased-data-signals-an-executive-playbook-to-certify-price-and-failover-third-party-feeds--71169500
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>144b77a7-02f5-4982-9a9c-f337e7652f63Wed, 08 Apr 2026 00:26:19 +0000Mirko PetersEnterprises rely on purchased data signals—identity graphs, geolocation, enrichment feeds, credit scores—to power decisions, yet these feeds bring hidden quality, licensing, privacy, and continuity risks. This 20‑minute executive monologue equips...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>576false39fullhttps://www.spreaker.com/episode/algorithmic-pricing-governance-a-c-suite-playbook-to-price-with-models-protect-margin-and-manage-fairness--71108491
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-38Sun, 05 Apr 2026 01:24:47 +0000Mirko PetersAlgorithmic pricing can turbocharge revenue but also quietly erode margin, invite regulatory scrutiny, and damage customer trust when incentives, data, or orchestration misalign. This 20‑minute executive monologue gives C‑level leaders a practical,...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>543false38fullhttps://www.spreaker.com/episode/model-concentration-risk-an-executive-playbook-to-measure-diversify-and-insure-single-point-ai-failures--70910662
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-37Fri, 27 Mar 2026 01:25:08 +0000Mirko PetersOrganizations increasingly rely on a small set of models, vendors, or datasets—creating concentration that can turn a single outage, vendor change, or model failure into enterprise-wide disruption. This 20‑minute executive monologue gives C-level...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>559false37fullhttps://www.spreaker.com/episode/revenue-forensics-an-executive-playbook-to-detect-attribute-and-stop-ai-driven-margin-leakage--70640798
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-36Sun, 15 Mar 2026 00:25:36 +0000Mirko PetersHidden margin leaks from AI—silent mis-calibrations, feedback loops, misrouted decisions, and integration drift—eat profitability long before dashboards raise alarms. This episode opens with a concise C-suite vignette where a personalization stack...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>507false36fullhttps://www.spreaker.com/episode/customer-redress-remediation-an-executive-playbook-for-funded-trust-preserving-responses-to-ai-failures--70630310
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-35Sat, 14 Mar 2026 00:24:48 +0000Mirko PetersAI failures inevitably touch customers—wrong decisions, unfair outcomes, privacy leaks, or harmful recommendations. Boards demand more than apologies: they need an auditable, funded remediation playbook that limits balance‑sheet exposure and repairs...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>558false35fullhttps://www.spreaker.com/episode/consent-as-code-an-executive-playbook-to-govern-customer-consent-lifecycles-for-ai--70615886
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-34Fri, 13 Mar 2026 00:26:10 +0000Mirko PetersCustomer consent is no longer a legal footnote—it’s the control plane that determines what AI systems can and cannot do. This episode opens with a concise C‑suite vignette where inconsistent consent handling forced a product rollback and regulatory...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>497false34fullhttps://www.spreaker.com/episode/reviewer-market-an-executive-playbook-to-build-a-scalable-internal-marketplace-for-human-oversight--70615881
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-33Fri, 13 Mar 2026 00:26:10 +0000Mirko PetersHuman review is still the safety valve for high‑stakes AI, but ad‑hoc review pools are costly, inconsistent, and invisible to finance. This episode opens with an executive vignette where inconsistent reviewer quality caused a regulatory complaint and...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>538false33fullhttps://www.spreaker.com/episode/feedback-loop-debt-an-executive-playbook-to-detect-quantify-control-self-reinforcing-ai-failures--70605194
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-32Thu, 12 Mar 2026 08:24:36 +0000Mirko PetersAdaptive models and live interventions can create feedback loops that silently amplify bias, inflate costs, or erode customer trust—often long before monitoring alarms ring. This episode opens with a short C‑suite vignette where a personalization...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>603false32fullhttps://www.spreaker.com/episode/decision-latency-budgets-an-executive-playbook-to-match-ai-speed-with-business-tempo--70582458
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-31Wed, 11 Mar 2026 00:25:55 +0000Mirko PetersExecutives fund accuracy and uptime but rarely budget for the other half of decision quality: latency. Wrong speed destroys outcomes—slow fraud decisions leak losses, instant personalization can trigger churn, and intermediate delays shift customer...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>543false31fullhttps://www.spreaker.com/episode/decision-value-chains-an-executive-playbook-to-map-attribute-govern-multi-model-outcomes--70558237
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-30Tue, 10 Mar 2026 00:26:01 +0000Mirko PetersEnterprises increasingly stitch many models—routing, ranking, personalization, fraud, pricing—into single customer journeys. When outcomes deviate, leaders need to know which model, data feed, or orchestration decision produced the impact and who must...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>569false30fullhttps://www.spreaker.com/episode/model-change-management-an-executive-playbook-for-safe-auditable-model-updates--70517659
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-29Sat, 07 Mar 2026 00:24:56 +0000Mirko PetersModel updates are routine engineering work until one upgrade misroutes revenue, exposes customer data, or breaks a compliance gate. This episode opens with a concise executive vignette where an uncoordinated model roll‑out cost weeks of remediation...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>532false29fullhttps://www.spreaker.com/episode/prompt-governance-an-executive-playbook-for-versioning-provenance-secure-prompting--70494695
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-28Fri, 06 Mar 2026 00:26:22 +0000Mirko PetersPrompt engineering is now an enterprise surface: prompts determine behavior, cost, and compliance across customer agents, copilots, and fine‑tuned flows—but prompt practices are rarely governed. This episode opens with a concise vignette where an...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>556false28fullhttps://www.spreaker.com/episode/litigation-readiness-an-executive-playbook-for-ai-related-lawsuits--70463022
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-27Thu, 05 Mar 2026 00:25:41 +0000Mirko PetersAI systems can create novel paths to legal exposure—consumer harm, discrimination suits, contract disputes, or regulatory enforcement—that escalate quickly if executives lack a prepared legal and operational response. This episode opens with a concise...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>521false27fullhttps://www.spreaker.com/episode/stand-up-an-ai-ethics-board-a-30-90-day-c-suite-playbook--70430284
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-26Wed, 04 Mar 2026 00:24:28 +0000Mirko PetersToo many organizations create advisory ethics groups that are polite but powerless. This episode opens with a short anonymized mini‑case: a product team ignored advisory recommendations, an algorithmic harm surfaced publicly, and remediation cost the...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>526false26fullhttps://www.spreaker.com/episode/ecosystem-ai-an-executive-playbook-for-shared-models-data-partnership-governance--70380429
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-25Mon, 02 Mar 2026 00:24:26 +0000Mirko PetersStrategic partnerships—joint ventures, channel integrations, data co-ops, and platform alliances—are where AI scale often happens, but they also create ambiguous ownership, data-usage friction, and misaligned incentives. In this 20-minute executive...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>713false25fullhttps://www.spreaker.com/episode/independent-assurance-an-executive-playbook-to-commission-fund-and-act-on-third-party-ai-audits--70367911
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-24Sun, 01 Mar 2026 00:26:45 +0000Mirko PetersInternal reviews are necessary but not sufficient: independent third‑party audits translate technical findings into credible, fundable actions for boards, auditors, and insurers. This 20‑minute decision-first monologue opens with a concise vignette...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>573false24fullhttps://www.spreaker.com/episode/insure-the-unknown-an-executive-playbook-for-transferring-ai-risk-with-insurance-warranties-bonds--70352728
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-23Sat, 28 Feb 2026 00:26:42 +0000Mirko PetersMany C-level leaders treat AI risk as internal control; few know how to transfer residual risk to insurance or structure warranties. This 20-minute executive monologue opens with a concise vignette where an algorithmic pricing error triggered a...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>751false23fullhttps://www.spreaker.com/episode/model-freshness-an-executive-playbook-for-recalibration-seasonality-and-model-aging--70218545
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-22Mon, 23 Feb 2026 00:24:33 +0000Mirko PetersModels degrade for predictable reasons—seasonality, shifting customer behavior, pipeline changes, and calendar-driven promotions—but executives rarely fund sustained freshness practices until revenue drifts. In this 20‑minute monologue Mirko opens...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>554false22fullhttps://www.spreaker.com/episode/model-marketplace-an-executive-playbook-to-catalog-certify-and-monetize-reusable-models--70172511
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-21Fri, 20 Feb 2026 06:25:16 +0000Mirko PetersEnterprises waste time, money, and trust when every team rebuilds similar models or reuses uncertified artifacts. This 20‑minute executive monologue opens with a concise vignette where duplicated churn-detection models produced inconsistent customer...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>570false21fullhttps://www.spreaker.com/episode/the-label-economy-an-executive-playbook-to-treat-labeling-as-a-strategic-asset--70144243
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-19Thu, 19 Feb 2026 08:25:49 +0000Mirko PetersHigh-quality labels are the unsung input that determines whether models deliver predictable business outcomes—or unpredictable risk. This 20‑minute executive monologue opens with a concise vignette where poor labeling inflated a fraud model’s false...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>530false19fullhttps://www.spreaker.com/episode/adoption-heatmaps-an-executive-playbook-to-map-friction-and-prioritize-ai-rollouts--70144242
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-20Thu, 19 Feb 2026 00:00:00 +0000Mirko PetersLarge technical proofs-of-concept fail not for lack of accuracy but because they collide with organizational friction: unclear decision owners, brittle data flows, regulatory constraints, and operational bottlenecks. This 20-minute executive monologue...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>499false20fullhttps://www.spreaker.com/episode/human-in-the-loop-at-scale-an-executive-playbook-to-fund-staff-and-govern-human-oversight-for-high-stakes-ai--70053298
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-18Sat, 14 Feb 2026 00:23:57 +0000Mirko PetersHigh-stakes AI still needs human judgment: content moderation, high-risk approvals, exception review, and safety triage all require reliable human oversight. Yet most organizations treat human review as ad hoc, underfunded, and invisible to risk...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>525false18fullhttps://www.spreaker.com/episode/regulatory-sandboxes-for-ai-an-executive-playbook-to-run-auditable-pilot-programs--70029360
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-17Fri, 13 Feb 2026 00:24:22 +0000Mirko PetersA vivid 20-minute executive primer that turns the abstract promise of a regulatory sandbox into executable actions and ready-to-use artifacts. It opens with a short, specific vignette where a fintech pilot surfaced biased pricing for a customer...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>660false17fullhttps://www.spreaker.com/episode/privacy-budget-an-executive-playbook-for-managing-data-exposure-in-enterprise-ai--70006312
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-16Thu, 12 Feb 2026 06:27:13 +0000Mirko PetersEnterprises routinely trade velocity for data exposure without an executive-level ledger to decide what to protect, monitor, or accept. In this 20-minute monologue Mirko introduces the 'Privacy Budget'—a simple, durable governance construct that...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>554false16fullhttps://www.spreaker.com/episode/fairness-debt-an-executive-playbook-to-detect-prioritize-and-remediate-unfair-ai--69965458
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-15Wed, 11 Feb 2026 00:26:03 +0000Mirko PetersAI systems accrue 'fairness debt'—undetected disparate impacts, buried trade-offs, and shadow remediation costs that compound as models scale. In this 20‑minute executive monologue Mirko opens with a concise vignette where a lending model’s hidden...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>520false15fullhttps://www.spreaker.com/episode/metric-debt-an-executive-playbook-to-audit-align-and-retire-metrics-that-break-ai--69908901
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-14Tue, 10 Feb 2026 00:26:22 +0000Mirko PetersOrganizations accumulate metric debt: dozens of overlapping KPIs, shifting definitions, and undocumented downstream consumers that cause model drift, perverse incentives, and repeated incidents. In this 20-minute monologue Mirko opens with a concise...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>749false14fullhttps://www.spreaker.com/episode/decision-contracts-turning-predictions-into-accountable-business-actions--69867409
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-13Sun, 08 Feb 2026 00:24:43 +0000Mirko PetersModels that emit scores rarely include the binding rules leaders need: who acts, when, at what threshold, and who pays for mistakes. In this 20‑minute executive monologue Mirko introduces ‘Decision Contracts’—compact, board‑readable agreements that...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>575false13fullhttps://www.spreaker.com/episode/incentives-that-stick-designing-executive-and-team-incentives-to-deliver-measurable-ai-outcomes--69851505
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-12Sat, 07 Feb 2026 00:25:08 +0000Mirko PetersToo many AI programs fail not for lack of models but because incentives push the wrong behavior: teams optimize vanity metrics, vendors chase one‑time uplift, and business owners avoid ownership of outcomes. In this 20‑minute executive monologue Mirko...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>672false12fullhttps://www.spreaker.com/episode/slos-for-ai-an-executive-playbook-to-define-monitor-and-enforce-model-data-service-level-objectives--69828128
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-11Fri, 06 Feb 2026 00:25:53 +0000Mirko PetersExecutives often demand reliability from AI but lack a shared language to measure it. In this 20-minute monologue Mirko opens with a concise vignette where unseen model latency and stale features caused revenue slippage, then delivers a compact,...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>538false11fullhttps://www.spreaker.com/episode/price-of-intelligence-an-executive-playbook-for-governing-algorithmic-pricing--69796360
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-10Thu, 05 Feb 2026 00:25:49 +0000Mirko PetersDynamic pricing can unlock margin and responsiveness, but when algorithmic prices misalign with customer expectations or regulation, revenue wins can turn into churn, complaints, and legal risk. In this 20‑minute executive monologue Mirko presents a...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>596false10fullhttps://www.spreaker.com/episode/causal-decisioning-how-leaders-prove-ai-drives-value--69773078
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-09Wed, 04 Feb 2026 00:24:48 +0000Mirko PetersMany leaders celebrate accurate models but can’t prove they change outcomes. In this 20‑minute episode Mirko opens with a vivid executive vignette: a personalization pilot that tripled engagement yet didn’t move revenue, and uses that story to frame a...
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>585analytics,artificialintelligence,behavior,causality,customers,datascience,decisioning,engagement,executives,experimentation,impact,innovation,insights,leadership,measurement,optimization,personalization,revenue,strategy,transformationfalse9fullhttps://www.spreaker.com/episode/synthetic-signals-an-executive-playbook-for-using-synthetic-data-to-unlock-enterprise-ai--69750795
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-08Tue, 03 Feb 2026 01:25:03 +0000Mirko PetersEnterprises routinely hit practical limits: unavailable or sensitive data, rare-event gaps, and slow procurement that stalls valuable AI projects. In this focused 20‑minute episode Mirko gives senior leaders a pragmatic, decision-first playbook for...
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>478analytics,artificialintelligence,automation,banking,compliance,datascience,decisionmaking,deployment,execution,fraud,governance,innovation,leadership,performance,privacy,procurement,scalability,strategy,syntheticdata,validationfalse8fullhttps://www.spreaker.com/episode/ai-in-the-deal-room-an-executive-playbook-for-m-a-due-diligence-and-post-merger-integration--69727151 (00:00:23) The Hidden Risk of Embedded AI in M&A
(00:01:52) Pre-Deal AI Due Diligence Checklist
(00:03:33) Fast Signals for Model and Data Health
(00:05:15) Translating Findings into Deal Mechanics
(00:06:46) Legal and IP Red Flags to Watch Out For
(00:08:13) 30-90 Day Integration Playbook
(00:10:58) Case Study: AI Integration Challenges
(00:11:53) Three Executive Actions for AI in M&A
(00:12:43) Mitigating AI Risks in Deals

Mergers and acquisitions routinely misprice or miss downstream costs of embedded AI: tangled data lineage, undocumented models, unenforceable IP claims, or regulatory exposures can turn strategic acquisitions into recurring liabilities. In this 20‑minute executive monologue Mirko delivers a decision‑first playbook for buyers and integration sponsors. He walks through focused AI due diligence (what to ask in 30–90 minutes of executive interviews), a lightweight technical checklist for validating model and data health without deep engineering work, legal and IP red flags to surface, and a prioritized post‑close integration plan that preserves optionality and reduces run-rate. Listeners get board‑ready metrics to translate technical findings into price adjustments and escrow triggers, negotiation levers to allocate remediation costs, and a 30–90 day integration roadmap to onboard models, align SLAs, and retire redundant pipelines. Practical, non‑technical, and immediately actionable for deal teams and executives. That’s the difference between models and value.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-07Mon, 02 Feb 2026 00:25:42 +0000Mirko PetersMergers and acquisitions routinely misprice or miss downstream costs of embedded AI: tangled data lineage, undocumented models, unenforceable IP claims, or regulatory exposures can turn strategic acquisitions into recurring liabilities. In this... (00:00:23) The Hidden Risk of Embedded AI in M&A
(00:01:52) Pre-Deal AI Due Diligence Checklist
(00:03:33) Fast Signals for Model and Data Health
(00:05:15) Translating Findings into Deal Mechanics
(00:06:46) Legal and IP Red Flags to Watch Out For
(00:08:13) 30-90 Day Integration Playbook
(00:10:58) Case Study: AI Integration Challenges
(00:11:53) Three Executive Actions for AI in M&A
(00:12:43) Mitigating AI Risks in Deals

Mergers and acquisitions routinely misprice or miss downstream costs of embedded AI: tangled data lineage, undocumented models, unenforceable IP claims, or regulatory exposures can turn strategic acquisitions into recurring liabilities. In this 20‑minute executive monologue Mirko delivers a decision‑first playbook for buyers and integration sponsors. He walks through focused AI due diligence (what to ask in 30–90 minutes of executive interviews), a lightweight technical checklist for validating model and data health without deep engineering work, legal and IP red flags to surface, and a prioritized post‑close integration plan that preserves optionality and reduces run-rate. Listeners get board‑ready metrics to translate technical findings into price adjustments and escrow triggers, negotiation levers to allocate remediation costs, and a 30–90 day integration roadmap to onboard models, align SLAs, and retire redundant pipelines. Practical, non‑technical, and immediately actionable for deal teams and executives. That’s the difference between models and value.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>842automation,business,decisionmaking,efficiency,entrepreneurship,execution,growth,innovation,leadership,management,mindset,operations,optimization,performance,productivity,profitability,scaling,strategy,systems,workflowfalse7fullhttps://www.spreaker.com/episode/sunset-clause-an-executive-playbook-for-retiring-ai-and-managing-model-debt--69712947 (00:00:24) The Hidden Dangers of AI System Retirement
(00:01:52) Identifying Retirement Signals in AI Models
(00:03:44) The Decision Rubric for Model Retirement
(00:05:48) Practical Blueprints for Model Transition
(00:06:48) Governance and Communication in Model Retirement
(00:08:30) Budgeting and Funding for Model Transitions
(00:09:19) Implementing a Model Retirement Process
(00:10:03) The 30-90 Day Model Retirement Playbook
(00:11:10) Closing Thoughts and Call to Action

AI lifecycles end as surely as they begin—yet most organizations lack an executive process to retire, replace, or repurpose models and datasets safely. In this focused monologue Mirko provides a decision‑first playbook that helps leaders identify retirement signals (drift, rising run-rate, opportunity cost, regulatory or contractual change), apply a pragmatic rubric balancing business value, risk, and technical debt, and run a prioritized decommissioning program. The episode covers stakeholder communication (internal owners, customers, regulators), legal and audit obligations for data retention and provenance, migration patterns (dual-run validation, phased rollback, staged sunset), and how to budget transitional costs so teams can stop subsidizing legacy systems. Listeners get a 30–90 day checklist to inventory candidates, cost ongoing run-rate vs replacement, define rollback and observability requirements, and embed retirement gates into governance. Practical, non‑technical, and action-oriented, this episode helps executives remove hidden liabilities and preserve strategic optionality.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-06Sun, 01 Feb 2026 00:26:07 +0000Mirko PetersAI lifecycles end as surely as they begin—yet most organizations lack an executive process to retire, replace, or repurpose models and datasets safely. In this focused monologue Mirko provides a decision‑first playbook that helps leaders identify... (00:00:24) The Hidden Dangers of AI System Retirement
(00:01:52) Identifying Retirement Signals in AI Models
(00:03:44) The Decision Rubric for Model Retirement
(00:05:48) Practical Blueprints for Model Transition
(00:06:48) Governance and Communication in Model Retirement
(00:08:30) Budgeting and Funding for Model Transitions
(00:09:19) Implementing a Model Retirement Process
(00:10:03) The 30-90 Day Model Retirement Playbook
(00:11:10) Closing Thoughts and Call to Action

AI lifecycles end as surely as they begin—yet most organizations lack an executive process to retire, replace, or repurpose models and datasets safely. In this focused monologue Mirko provides a decision‑first playbook that helps leaders identify retirement signals (drift, rising run-rate, opportunity cost, regulatory or contractual change), apply a pragmatic rubric balancing business value, risk, and technical debt, and run a prioritized decommissioning program. The episode covers stakeholder communication (internal owners, customers, regulators), legal and audit obligations for data retention and provenance, migration patterns (dual-run validation, phased rollback, staged sunset), and how to budget transitional costs so teams can stop subsidizing legacy systems. Listeners get a 30–90 day checklist to inventory candidates, cost ongoing run-rate vs replacement, define rollback and observability requirements, and embed retirement gates into governance. Practical, non‑technical, and action-oriented, this episode helps executives remove hidden liabilities and preserve strategic optionality.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>730advantage,alignment,capability,confidence,decisions,execution,impact,leadership,longevity,maturity,momentum,outcomes,ownership,priorities,resilience,roadmap,scale,strategy,sustainability,transformationfalse6fullhttps://www.spreaker.com/episode/ai-on-the-balance-sheet-a-board-playbook-for-measurable-risk--69685611 (00:00:27) AI on the Balance Sheet: A Boardroom Perspective
(00:00:45) The Six Million Dollar Model Error
(00:01:18) Translating Model Risk into ERM Language
(00:02:15) Unpacking the Mini Case: A Step-by-Step Analysis
(00:03:06) Mapping AI Risk to ERM Categories
(00:03:51) Key Metrics for AI Risk Assessment
(00:05:11) Mitigating AI Risk: Three Levers
(00:05:58) Leadership and Decision Rights in AI Risk Management
(00:06:44) A Prioritized Playbook for AI Risk Management

Boards often treat AI as a technical issue rather than a balance-sheet exposure. In this 20-minute executive monologue Mirko reframes AI as an enterprise risk that must be managed inside ERM. The episode opens with a concrete mini-case — a hypothetical pricing-model error that shaved 3% off a quarterly revenue number (for example, roughly $6M on a $200M quarter) — to show how model failures translate to dollars and timelines. Mirko then walks executives through mapping model, data, vendor, and operational risks to standard ERM categories and translates key metrics into plain English (e.g., loss-velocity = how fast an error becomes a financial loss). Listeners receive a prioritized 30–90 day playbook and a downloadable AI-ERM Board Pack: one-page PDF heatmap, Excel metric template, and checklist to use with audit committees. Tone is pragmatic and executive-first: convert technical gaps into budget asks, insurance choices, and clear decision rights.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-05Fri, 30 Jan 2026 14:25:04 +0000Mirko PetersBoards often treat AI as a technical issue rather than a balance-sheet exposure. In this 20-minute executive monologue Mirko reframes AI as an enterprise risk that must be managed inside ERM. The episode opens with a concrete mini-case — a... (00:00:27) AI on the Balance Sheet: A Boardroom Perspective
(00:00:45) The Six Million Dollar Model Error
(00:01:18) Translating Model Risk into ERM Language
(00:02:15) Unpacking the Mini Case: A Step-by-Step Analysis
(00:03:06) Mapping AI Risk to ERM Categories
(00:03:51) Key Metrics for AI Risk Assessment
(00:05:11) Mitigating AI Risk: Three Levers
(00:05:58) Leadership and Decision Rights in AI Risk Management
(00:06:44) A Prioritized Playbook for AI Risk Management

Boards often treat AI as a technical issue rather than a balance-sheet exposure. In this 20-minute executive monologue Mirko reframes AI as an enterprise risk that must be managed inside ERM. The episode opens with a concrete mini-case — a hypothetical pricing-model error that shaved 3% off a quarterly revenue number (for example, roughly $6M on a $200M quarter) — to show how model failures translate to dollars and timelines. Mirko then walks executives through mapping model, data, vendor, and operational risks to standard ERM categories and translates key metrics into plain English (e.g., loss-velocity = how fast an error becomes a financial loss). Listeners receive a prioritized 30–90 day playbook and a downloadable AI-ERM Board Pack: one-page PDF heatmap, Excel metric template, and checklist to use with audit committees. Tone is pragmatic and executive-first: convert technical gaps into budget asks, insurance choices, and clear decision rights.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>587accountability,benchmarking,cost,decisions,economics,efficiency,forecasting,impact,investment,measurement,metrics,outcomes,performance,prioritization,returns,roi,scaling,tradeoffs,transparency,valuefalse5fullhttps://www.spreaker.com/episode/buying-the-brain-an-executive-playbook-for-procuring-foundation-models-and-managing-tco--69684225 (00:00:29) The Hidden Costs of AI Pilots
(00:02:30) Mapping Outcomes to Sourcing Strategies
(00:03:52) Four Common Approaches to Foundation Models
(00:04:37) Legal and Procurement Checklist
(00:05:18) Total Cost of Ownership Considerations
(00:06:41) Data Rights and Exit Clauses
(00:07:29) Operational and Security Considerations
(00:08:05) Organizational Implications and Procurement Cadence
(00:08:39) 30-Day Checklist for Procurement

Large language and multimodal foundation models offer capability leaps but introduce complex procurement, cost, and legal trade-offs that routinely stall enterprise adoption. In this monologue Mirko lays out a pragmatic executive playbook for buying—versus building—foundation models responsibly. The episode covers how to scope business outcomes, compare licensing models (hosted API, private deployment, fine-tuning), map true TCO (compute, data ops, monitoring, latency/SLA costs), assign contractual risk (data ownership, IP, reverse-engineering, security), and design exit and portability clauses before signing. Mirko uses concise, anonymized vignettes to show common procurement pitfalls and executive negotiation levers that protect margin and compliance. Listeners receive a prioritized 30–90 day checklist to assess current contracts, power conversations with procurement and legal, and a simple decision rubric to choose the model sourcing approach that aligns with strategy and risk appetite. Practical, non-technical, and board-ready guidance for leaders who must buy capability without buying long-term surprise costs.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-04Fri, 30 Jan 2026 00:00:00 +0000Mirko PetersLarge language and multimodal foundation models offer capability leaps but introduce complex procurement, cost, and legal trade-offs that routinely stall enterprise adoption. In this monologue Mirko lays out a pragmatic executive playbook for... (00:00:29) The Hidden Costs of AI Pilots
(00:02:30) Mapping Outcomes to Sourcing Strategies
(00:03:52) Four Common Approaches to Foundation Models
(00:04:37) Legal and Procurement Checklist
(00:05:18) Total Cost of Ownership Considerations
(00:06:41) Data Rights and Exit Clauses
(00:07:29) Operational and Security Considerations
(00:08:05) Organizational Implications and Procurement Cadence
(00:08:39) 30-Day Checklist for Procurement

Large language and multimodal foundation models offer capability leaps but introduce complex procurement, cost, and legal trade-offs that routinely stall enterprise adoption. In this monologue Mirko lays out a pragmatic executive playbook for buying—versus building—foundation models responsibly. The episode covers how to scope business outcomes, compare licensing models (hosted API, private deployment, fine-tuning), map true TCO (compute, data ops, monitoring, latency/SLA costs), assign contractual risk (data ownership, IP, reverse-engineering, security), and design exit and portability clauses before signing. Mirko uses concise, anonymized vignettes to show common procurement pitfalls and executive negotiation levers that protect margin and compliance. Listeners receive a prioritized 30–90 day checklist to assess current contracts, power conversations with procurement and legal, and a simple decision rubric to choose the model sourcing approach that aligns with strategy and risk appetite. Practical, non-technical, and board-ready guidance for leaders who must buy capability without buying long-term surprise costs.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>690accountability,assurance,compliance,confidence,controls,ethics,governance,oversight,policies,regulation,reliability,resilience,responsibility,risk,safeguards,scale,security,stewardship,transparency,trustfalse4fullhttps://www.spreaker.com/episode/ai-incident-simulations-a-c-suite-playbook-for-preparing-responding-and-learning--69606574 (00:00:26) The Importance of AI Incident Simulations
(00:02:22) Four High-Impact AI Scenario Families
(00:03:32) Designing Effective Tabletop Exercises
(00:04:05) Defining Decision Gates and Roles
(00:05:52) Measuring Readiness and Post-Mortems
(00:07:28) Implementing a 90-Day Rollout Plan
(00:08:13) Actionable Steps and Closing Remarks
(00:08:53) Downloadable Resources
(00:09:26) Subscription and Next Episode

Organizations prepare for cyber incidents but rarely rehearse AI-specific failures—model drift, hallucinations in customer agents, pricing errors, or biased automated decisions. In this monologue Mirko delivers a practical C‑suite playbook for designing and running AI incident simulations and tabletop exercises that make abstract risks operationally manageable. He explains how to choose scenario scope and severity, create realistic triggers, assign clear decision gates and escalation paths, coordinate legal/comms/regulatory playbooks, and measure readiness with board-ready metrics. Through concise anonymized vignettes Mirko highlights trade-offs (high-impact/low-probability vs frequent operational faults) and shows how to convert exercise outcomes into governance changes, funding requests, and measurable SLA improvements. Listeners receive a prioritized 30–90 day rollout plan, a tabletop script template, and guidance for turning simulations into continuous improvement. This episode is for executives who need AI systems that are resilient, auditable, and decision-ready without adding bureaucracy.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-02Tue, 27 Jan 2026 00:25:24 +0000Mirko PetersOrganizations prepare for cyber incidents but rarely rehearse AI-specific failures—model drift, hallucinations in customer agents, pricing errors, or biased automated decisions. In this monologue Mirko delivers a practical C‑suite playbook for... (00:00:26) The Importance of AI Incident Simulations
(00:02:22) Four High-Impact AI Scenario Families
(00:03:32) Designing Effective Tabletop Exercises
(00:04:05) Defining Decision Gates and Roles
(00:05:52) Measuring Readiness and Post-Mortems
(00:07:28) Implementing a 90-Day Rollout Plan
(00:08:13) Actionable Steps and Closing Remarks
(00:08:53) Downloadable Resources
(00:09:26) Subscription and Next Episode

Organizations prepare for cyber incidents but rarely rehearse AI-specific failures—model drift, hallucinations in customer agents, pricing errors, or biased automated decisions. In this monologue Mirko delivers a practical C‑suite playbook for designing and running AI incident simulations and tabletop exercises that make abstract risks operationally manageable. He explains how to choose scenario scope and severity, create realistic triggers, assign clear decision gates and escalation paths, coordinate legal/comms/regulatory playbooks, and measure readiness with board-ready metrics. Through concise anonymized vignettes Mirko highlights trade-offs (high-impact/low-probability vs frequent operational faults) and shows how to convert exercise outcomes into governance changes, funding requests, and measurable SLA improvements. Listeners receive a prioritized 30–90 day rollout plan, a tabletop script template, and guidance for turning simulations into continuous improvement. This episode is for executives who need AI systems that are resilient, auditable, and decision-ready without adding bureaucracy.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>586accountability,alignment,coordination,delivery,execution,governance,incentives,leadership,maturity,operating,outcomes,ownership,processes,roles,scale,structure,talent,teams,velocity,workflowfalse2fullhttps://www.spreaker.com/episode/data-products-as-a-business-pricing-funding-and-incentives-for-sustainable-ai--69621519 (00:00:25) The Problem of Unsustainable AI Models
(00:01:56) Four Internal Pricing Patterns for Data Products
(00:04:33) Funding Models for Data Platforms
(00:06:22) Governance and Incentives for Data Products
(00:07:55) Practical Vignettes and Lessons Learned
(00:09:13) Board-Ready KPIs for Data Products
(00:09:53) 30-Day Rollout Plan for Data Products
(00:11:05) Final Thoughts and Call to Action
(00:12:21) Resources and Templates

Enterprises routinely treat data work as an engineering cost center, which starves successful models of funding and leaves high-impact capabilities stalled. In this episode Mirko presents an executive playbook for treating data outputs as products with deliberate pricing, funding models, and incentive structures so AI delivers repeatable value. The episode explains internal pricing patterns (cost-recovery, value-based, subscription, showback), funding strategies (central platform budget, product line capex, outcome-based KPIs), and governance that aligns product managers, platform teams, and business sponsors. Mirko uses concise, anonymized vignettes to show trade-offs—when to subsidize early-stage features, how to avoid perverse incentives, and which board-level KPIs to demand. Listeners receive a prioritized 30–90 day rollout checklist to pilot an internal pricing model, plus templates for a funding proposal and SLA that make data products visible and investable. This is practical guidance for leaders who must turn technical capability into a business asset without adding bureaucracy.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-03Tue, 27 Jan 2026 00:00:00 +0000Mirko PetersEnterprises routinely treat data work as an engineering cost center, which starves successful models of funding and leaves high-impact capabilities stalled. In this episode Mirko presents an executive playbook for treating data outputs as products... (00:00:25) The Problem of Unsustainable AI Models
(00:01:56) Four Internal Pricing Patterns for Data Products
(00:04:33) Funding Models for Data Platforms
(00:06:22) Governance and Incentives for Data Products
(00:07:55) Practical Vignettes and Lessons Learned
(00:09:13) Board-Ready KPIs for Data Products
(00:09:53) 30-Day Rollout Plan for Data Products
(00:11:05) Final Thoughts and Call to Action
(00:12:21) Resources and Templates

Enterprises routinely treat data work as an engineering cost center, which starves successful models of funding and leaves high-impact capabilities stalled. In this episode Mirko presents an executive playbook for treating data outputs as products with deliberate pricing, funding models, and incentive structures so AI delivers repeatable value. The episode explains internal pricing patterns (cost-recovery, value-based, subscription, showback), funding strategies (central platform budget, product line capex, outcome-based KPIs), and governance that aligns product managers, platform teams, and business sponsors. Mirko uses concise, anonymized vignettes to show trade-offs—when to subsidize early-stage features, how to avoid perverse incentives, and which board-level KPIs to demand. Listeners receive a prioritized 30–90 day rollout checklist to pilot an internal pricing model, plus templates for a funding proposal and SLA that make data products visible and investable. This is practical guidance for leaders who must turn technical capability into a business asset without adding bureaucracy.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>818alignment,architecture,data,enablement,execution,foundations,governance,infrastructure,integration,maturity,operations,ownership,pipelines,platforms,quality,reliability,scale,security,systems,velocityfalse3fullhttps://www.spreaker.com/episode/scaling-ai-an-executive-playbook-for-measurable-roi--69558683 (00:00:41) The Problem with Orphaned Pilots
(00:01:41) Aligning KPIs for Business Impact
(00:02:54) Productizing Your Model
(00:03:59) Ownership, Funding, and Governance
(00:05:01) Measuring ROI and Risk
(00:05:37) A Retail Case Study
(00:06:17) Leadership and Organizational Implications
(00:06:58) Practical Checklist and Negotiation Tips
(00:07:39) Closing Thoughts and Call to Action

Many enterprises stall after promising AI pilots because experiments lack product rigor, clear ownership, and instrumented ROI. In this episode Mirko delivers a compact, practical playbook for executives to convert pilots into repeatable, revenue-driving products. He focuses on the decisions leaders must make: aligning outcome-level KPIs to business objectives, designing a minimum viable model product with deployment and monitoring, establishing funding and governance, and instrumenting ROI and risk from day one. To ground the framework, Mirko shares an anonymized vignette: a retail client that cut stockouts by 12% and improved gross margin by 3% within six months after productizing a demand-forecast model. Listeners will leave with a prioritized 90-day checklist, negotiation language to secure executive buy-in, and a concrete CTA to download a two-page AI Scaling Checklist. This episode avoids code-level how-tos and vendor hype, concentrating on leadership moves that produce measurable value.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>datascienceshow-episode-01Fri, 23 Jan 2026 13:08:02 +0000Mirko PetersMany enterprises stall after promising AI pilots because experiments lack product rigor, clear ownership, and instrumented ROI. In this episode Mirko delivers a compact, practical playbook for executives to convert pilots into repeatable,... (00:00:41) The Problem with Orphaned Pilots
(00:01:41) Aligning KPIs for Business Impact
(00:02:54) Productizing Your Model
(00:03:59) Ownership, Funding, and Governance
(00:05:01) Measuring ROI and Risk
(00:05:37) A Retail Case Study
(00:06:17) Leadership and Organizational Implications
(00:06:58) Practical Checklist and Negotiation Tips
(00:07:39) Closing Thoughts and Call to Action

Many enterprises stall after promising AI pilots because experiments lack product rigor, clear ownership, and instrumented ROI. In this episode Mirko delivers a compact, practical playbook for executives to convert pilots into repeatable, revenue-driving products. He focuses on the decisions leaders must make: aligning outcome-level KPIs to business objectives, designing a minimum viable model product with deployment and monitoring, establishing funding and governance, and instrumenting ROI and risk from day one. To ground the framework, Mirko shares an anonymized vignette: a retail client that cut stockouts by 12% and improved gross margin by 3% within six months after productizing a demand-forecast model. Listeners will leave with a prioritized 90-day checklist, negotiation language to secure executive buy-in, and a concrete CTA to download a two-page AI Scaling Checklist. This episode avoids code-level how-tos and vendor hype, concentrating on leadership moves that produce measurable value.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>571analysis,business,cost,data,decisions,funding,granger,growth,impact,innovation,insights,metrics,model,models,product,risk,scaling,science,strategy,valuefalse1fullhttps://www.spreaker.com/episode/4-data-modeling-mistakes-that-break-data-pipelines-at-scale--68970118

• Why slow dashboards are usually caused by bad data models—not slow warehouses
• How cumulative tables eliminate repeated heavy computation
• The importance of fact table grain, surrogate keys, and time-based partitioning
• Why row explosion from time modeling destroys performance
• When graph modeling beats relational joins for fraud, networks, and dependencies
• How to shift compute from query-time to design-time
• How proper modeling leads to:
  • Faster dashboards
  • Predictable cloud costs
  • Stable KPIs
  • Fewer data incidents

🛠 The 4 Data Modeling Mistakes Covered 1️⃣ Skipping Cumulative Tables Why daily KPIs should never be recomputed from raw events—and how pre-aggregation stabilizes performance, cost, and governance. 2️⃣ Broken Fact Table Design How unclear grain, missing surrogate keys, and lack of partitioning create duplicate revenue, unstable joins, and exploding cloud bills. 3️⃣ Time Modeling with Row Explosion Why expanding date ranges into one row per day destroys efficiency—and how period-based modeling with date arrays fixes it. 4️⃣ Forcing Graph Problems into Relational Tables Why fraud, recommendations, and network analysis break SQL—and when graph modeling is the right tool. 🎯 Who This Episode Is For

• Data Engineers
• Analytics Engineers
• Data Architects
• BI Engineers
• Machine Learning Engineers
• Platform & Infrastructure Teams
• Anyone scaling analytics beyond prototype stage

🚀 Why This Matters Most pipelines don’t fail because jobs crash—they fail because they’re:

• Slow
• Expensive
• Semantically inconsistent
• Impossible to trust at scale

This episode shows how modeling discipline—not tooling hype—is what actually keeps pipelines fast, cheap, and reliable. ✅ Core Takeaway Shift compute to design-time. Encode meaning into your data model. Remove repeated work from the hot path. That’s how you scale data without scaling chaos.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>https://api.spreaker.com/episode/68970118Wed, 10 Dec 2025 13:00:08 +0000Mirko PetersSlow dashboards, runaway cloud costs, and broken KPIs aren’t usually tooling problems—they’re data modeling problems. In this episode, I break down the four most damaging data modeling mistakes that silently destroy performance, reliability, and trust...

• Why slow dashboards are usually caused by bad data models—not slow warehouses
• How cumulative tables eliminate repeated heavy computation
• The importance of fact table grain, surrogate keys, and time-based partitioning
• Why row explosion from time modeling destroys performance
• When graph modeling beats relational joins for fraud, networks, and dependencies
• How to shift compute from query-time to design-time
• How proper modeling leads to:
  • Faster dashboards
  • Predictable cloud costs
  • Stable KPIs
  • Fewer data incidents

🛠 The 4 Data Modeling Mistakes Covered 1️⃣ Skipping Cumulative Tables Why daily KPIs should never be recomputed from raw events—and how pre-aggregation stabilizes performance, cost, and governance. 2️⃣ Broken Fact Table Design How unclear grain, missing surrogate keys, and lack of partitioning create duplicate revenue, unstable joins, and exploding cloud bills. 3️⃣ Time Modeling with Row Explosion Why expanding date ranges into one row per day destroys efficiency—and how period-based modeling with date arrays fixes it. 4️⃣ Forcing Graph Problems into Relational Tables Why fraud, recommendations, and network analysis break SQL—and when graph modeling is the right tool. 🎯 Who This Episode Is For

• Data Engineers
• Analytics Engineers
• Data Architects
• BI Engineers
• Machine Learning Engineers
• Platform & Infrastructure Teams
• Anyone scaling analytics beyond prototype stage

🚀 Why This Matters Most pipelines don’t fail because jobs crash—they fail because they’re:

• Slow
• Expensive
• Semantically inconsistent
• Impossible to trust at scale

This episode shows how modeling discipline—not tooling hype—is what actually keeps pipelines fast, cheap, and reliable. ✅ Core Takeaway Shift compute to design-time. Encode meaning into your data model. Remove repeated work from the hot path. That’s how you scale data without scaling chaos.

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>1599aggregation,analytics,architecture,bi,bigdata,cloudcosts,dataengineering,datamodeling,facttables,fraud,governance,graphdata,metrics,optimization,performance,pipelines,scalability,sql,timeseries,warehousesfalsefullhttps://www.spreaker.com/episode/the-secret-to-thriving-as-an-ai-entrepreneur--68938295study data to make better choices.* Add AI to your main business activities. Plan well and use good data to get better outcomes.* Learn about new AI ideas and tools. Keep up with news and try new things to stay ahead.* Create a team that supports AI. Teach, work together, and celebrate wins to encourage new ideas.* Plan for future success with AI. Match AI uses with your goals and set rules for fair use.What Is an AI-Powered Entrepreneur?Defining the AI-Powered EntrepreneurLet’s start with the basics. An AI-Powered Entrepreneur is someone who uses artificial intelligence tools to run their business smarter, faster, and more efficiently. Instead of relying on traditional methods, they integrate AI into their workflows to automate tasks, analyze data, and make better decisions. Think of it as having a supercharged assistant that never sleeps.For example, imagine using AI to handle customer service, create marketing campaigns, or even predict future trends in your industry. It’s not just about saving time—it’s about unlocking possibilities that were once out of reach. As an AI-Powered Entrepreneur, you’re not just running a business; you’re building a system that evolves and improves over time.Why AI Is Essential for Modern EntrepreneursWhy is AI such a game-changer? Let me break it down:* AI enhances decision-making by analyzing complex datasets faster and more accurately than humans.* It automates routine tasks, freeing up time for creative and strategic activities.* AI identifies trends and opportunities that traditional methods might miss, driving innovation.In today’s fast-paced world, these advantages aren’t optional—they’re essential. Without AI, you risk falling behind competitors who are already using it to scale their businesses.The Competitive Advantage of AI in BusinessAI doesn’t just level the playing field; it tilts it in your favor. Businesses that embrace AI gain a competitive edge across industries. Here’s how:These examples show how AI transforms industries, making businesses more efficient, profitable, and customer-focused. As an AI-Powered Entrepreneur, you’re not just keeping up—you’re leading the charge.Why Now Is the Time to Embrace AIThe Rapid Evolution of AI TechnologiesAI is evolving at a breakneck pace, and it's reshaping the way we do business. You might wonder how fast things are changing. Well, AI-powered image recognition is now helping us analyze historical relics and even restore damaged artifacts. It's like having a digital archaeologist at your fingertips. AI-based spectral imaging is revealing hidden layers in texts and artworks, offering new insights into lost historical details. And let's not forget machine learning algorithms that analyze economic data from past centuries to predict trade trends and financial crises. These advancements highlight AI's role in understanding historical patterns and shaping the future.How AI Is Disrupting Traditional IndustriesAI is not just a buzzword; it's a game-changer across various sectors. Here’s a quick rundown of how it's shaking things up:* Market Research: AI tools like sentiment analysis and predictive analytics are providing real-time insights, making market research more dynamic.* Content Creation: By analyzing consumer behavior, AI creates personalized content that optimizes engagement.* Advertising: Programmatic advertising and real-time bidding powered by AI improve targeting and efficiency.* E-commerce: AI personalizes recommendations and assists in inventory management, boosting sales.* Healthcare: Predictive analytics in AI tools enhance diagnostics and treatment outcomes.* Finance: Robo-advisors and fraud detection powered by AI reduce costs and improve efficiency.These examples show that AI is not just enhancing industries; it's transforming them. As an AI-Powered Entrepreneur, you can leverage these tools to stay ahead of the curve.The Risks of Falling Behind in an AI-Driven MarketFalling behind in an AI-driven market is a risk no business can afford. The statistics speak for themselves:Emerging data indicates a significant talent shortage in AI-related fields. Over 80% of business leaders are concerned about finding the necessary talent in the upcoming year. This highlights the risks associated with falling behind in an AI-driven market. Companies may struggle to implement AI solutions effectively without the necessary skilled workforce. AI has transitioned from a behind-the-scenes tool to a critical component in market research and campaign execution. The cost-effectiveness of AI solutions poses a risk for marketers who do not adapt quickly.Key Strategies for Thriving as an AI-Powered EntrepreneurLeveraging AI Tools for Efficiency and GrowthIf you’re like me, you’re always looking for ways to save time and get more done. That’s where AI tools come in. They’re not just fancy gadgets—they’re game-changers for efficiency and growth. Imagine having a tool that handles repetitive tasks, analyzes data, and even predicts trends. Sounds like a dream, right? But it’s real, and it’s happening now.Here’s how businesses are using AI tools to transform their operations:* Boosting productivity by automating routine tasks like data entry and scheduling.* Using advanced analytics to uncover valuable insights and make smarter decisions.* Strengthening customer relationships with AI-powered CRM systems.* Optimizing marketing efforts with automated solutions that target the right audience.* Enhancing sales performance with AI-driven forecasting tools.For example, I’ve seen companies use AI to improve customer engagement and satisfaction. Tools like chatbots provide instant responses, while data analysis tools help businesses understand what their customers really want. The result? Happier customers and higher revenue.The global AI market is growing fast—it’s expected to hit $243.70 billion by 2025. Businesses using AI solutions report a 40% increase in operational efficiency and a 25% boost in revenue. If that’s not a reason to dive in, I don’t know what is.Integrating AI into Core Business OperationsLet’s talk about the big picture. It’s not enough to use AI tools here and there. To truly thrive as an AI-Powered Entrepreneur, you need to integrate AI into the core of your business. Think of it as weaving AI into the fabric of your operations.Here’s a simple roadmap to get started:* Develop a Clear AI Strategy: Align your AI goals with your business objectives. What do you want to achieve? More sales? Better customer service? Start there.* Invest in Data Quality: AI thrives on data, but not just any data. High-quality, well-organized data is essential for AI to work its magic.* Foster Cross-Functional Collaboration: Get your teams involved early. When everyone works together, the integration process becomes smoother and more effective.Take PepsiCo, for example. They involved their teams early in the AI adoption process, and it paid off big time. By integrating AI into their marketing strategies, they achieved better results and streamlined their operations.When you integrate AI into your core business, you’re not just improving efficiency—you’re setting the stage for long-term success. Whether it’s automating HR tasks to attract top talent or using AI for financial decision-making, the possibilities are endless.Staying Ahead of AI Trends and InnovationsAI is evolving at lightning speed. Staying ahead of the curve isn’t just a nice-to-have—it’s a must. As an AI-Powered Entrepreneur, you need to keep your finger on the pulse of the latest trends and innovations.Here’s what I recommend:* Follow industry news and reports. For

Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:163923375Mon, 19 May 2025 14:16:17 +0000Mirko PetersAI is changing the game for entrepreneurs like never before. Imagine using tools that boost your marketing ROI by 20% or cut costs by 32%. That’s not just theory—it’s happening now. Companies using AI-driven personalization see a 40% jump in order...study data to make better choices.* Add AI to your main business activities. Plan well and use good data to get better outcomes.* Learn about new AI ideas and tools. Keep up with news and try new things to stay ahead.* Create a team that supports AI. Teach, work together, and celebrate wins to encourage new ideas.* Plan for future success with AI. Match AI uses with your goals and set rules for fair use.What Is an AI-Powered Entrepreneur?Defining the AI-Powered EntrepreneurLet’s start with the basics. An AI-Powered Entrepreneur is someone who uses artificial intelligence tools to run their business smarter, faster, and more efficiently. Instead of relying on traditional methods, they integrate AI into their workflows to automate tasks, analyze data, and make better decisions. Think of it as having a supercharged assistant that never sleeps.For example, imagine using AI to handle customer service, create marketing campaigns, or even predict future trends in your industry. It’s not just about saving time—it’s about unlocking possibilities that were once out of reach. As an AI-Powered Entrepreneur, you’re not just running a business; you’re building a system that evolves and improves over time.Why AI Is Essential for Modern EntrepreneursWhy is AI such a game-changer? Let me break it down:* AI enhances decision-making by analyzing complex datasets faster and more accurately than humans.* It automates routine tasks, freeing up time for creative and strategic activities.* AI identifies trends and opportunities that traditional methods might miss, driving innovation.In today’s fast-paced world, these advantages aren’t optional—they’re essential. Without AI, you risk falling behind competitors who are already using it to scale their businesses.The Competitive Advantage of AI in BusinessAI doesn’t just level the playing field; it tilts it in your favor. Businesses that embrace AI gain a competitive edge across industries. Here’s how:These examples show how AI transforms industries, making businesses more efficient, profitable, and customer-focused. As an AI-Powered Entrepreneur, you’re not just keeping up—you’re leading the charge.Why Now Is the Time to Embrace AIThe Rapid Evolution of AI TechnologiesAI is evolving at a breakneck pace, and it's reshaping the way we do business. You might wonder how fast things are changing. Well, AI-powered image recognition is now helping us analyze historical relics and even restore damaged artifacts. It's like having a digital archaeologist at your fingertips. AI-based spectral imaging is revealing hidden layers in texts and artworks, offering new insights into lost historical details. And let's not forget machine learning algorithms that analyze economic data...]]>5413falsefullhttps://www.spreaker.com/episode/why-ignoring-data-lineage-could-derail-your-ai-projects--68938296Data lineage is like a map that shows the journey of your data from its origin to its final destination. It’s not just about where the data comes from but also how it transforms along the way. Think of it as a detailed record of every stop your data makes, every change it undergoes, and every system it passes through.Here’s a quick breakdown to make it clearer:Why does this matter? Without understanding data lineage, you’re flying blind. You can’t ensure transparency, improve data quality, or meet compliance standards.Key Components of Data LineageNow, let’s talk about what makes up data lineage. It’s not just one thing—it’s a combination of several elements working together.* IT systems: These are the platforms where data gets transformed and integrated.* Business processes: Activities like data processing often reference related applications.* Data elements: These are the building blocks of lineage, defined at conceptual, logical, and physical levels.* Data checks and controls: These ensure data integrity, as outlined by industry standards.* Legislative requirements: Regulations like GDPR demand proper data processing and reporting.* Metadata: This describes everything else about the data, helping us understand its lineage better.When all these components come together, they create a framework that ensures your data is reliable, traceable, and compliant.The Role of AI-Powered Data LineageHere’s where things get exciting. AI-powered data lineage takes traditional lineage tracking to the next level. It uses automation to map out data transformations across complex systems, including multi-cloud environments.Imagine trying to track data manually across dozens of platforms—it’s nearly impossible. AI-powered systems handle this effortlessly, improving governance, compliance, and operational efficiency. Automated lineage tracking doesn’t just save time; it also boosts transparency and reliability.Organizations using AI-powered data lineage report fewer errors and better decision-making. It’s a game-changer for anyone dealing with large-scale data operations.Why AI Developers Should Prioritize Data LineageEnsuring Transparency and AccountabilityWhen it comes to building trust in AI, transparency and accountability are non-negotiable. As an AI developer, I’ve seen how data lineage plays a pivotal role in achieving both. It’s like having a detailed map that shows every twist and turn your data takes. This map ensures that every decision made by your AI system can be traced back to its source.Here’s why this matters. Imagine you’re asked to explain why your AI made a specific prediction. Without data lineage, you’re left guessing. But with it, you can confidently show the origin of the data, how it was processed, and why the AI reached its conclusion. This level of transparency builds trust with stakeholders and customers.Take a look at this:Transparency isn’t just about meeting regulations. It’s about showing that your AI systems are reliable and trustworthy. And when you add accountability into the mix, you’re creating a foundation for effective AI governance.Supporting Ethical AI PracticesEthical AI isn’t just a buzzword—it’s a responsibility. As AI developers, we have to ensure that our systems don’t unintentionally harm users or reinforce biases. This is where data lineage becomes a game-changer. By tracking every step of the data journey, we gain visibility and control over the inputs shaping our AI systems.Here’s what I’ve learned:* Data lineage enhances visibility and control in AI systems.* It supports the creation of trustworthy and compliant AI systems.* Improved data quality leads to more reliable AI-driven decisions.* It reduces risks associated with AI deployment.* It increases operational efficiency, enabling responsible AI usage.When we prioritize data lineage, we’re not just improving our systems—we’re protecting the people who rely on them. Ethical AI practices start with understanding the data, and lineage provides the clarity we need to make responsible decisions.Meeting Compliance and Regulatory StandardsRegulations like GDPR and CCPA aren’t just legal hurdles—they’re essential for protecting user data and ensuring fair practices. As an AI developer, I’ve seen how robust data lineage practices make it easier to demonstrate compliance with these regulations.For example, data lineage provides a documented record of every transformation and usage of data. This is critical for meeting the requirements of GDPR, HIPAA, and SOX. A 2022 Deloitte survey even found that organizations with strong data governance practices achieved 30% higher success rates in governance initiatives.Here’s why this matters:* Data lineage ensures you can demonstrate compliance with regulations.* It provides a clear audit trail, which is essential for regulatory compliance.* It helps organizations avoid penalties and maintain trust with stakeholders.When you prioritize data lineage, you’re not just ticking a box for compliance. You’re building a system that’s transparent, accountable, and trustworthy. And in today’s world, that’s what sets successful AI developers apart.Risks of Neglecting Data Lineage in AI ProjectsPoor Data Quality and Its ConsequencesI’ve seen firsthand how poor data quality can derail even the most promising AI projects. When data lineage is ignored, inconsistencies, missing values, and biases creep into datasets. These issues don’t just stay hidden—they snowball into bigger problems. For example, Zillow’s $306 million loss from its AI-driven home-buying program stemmed from flawed data predictions. That’s a staggering consequence of neglecting data integrity.The financial toll of poor data quality is massive. Businesses in the U.S. lose $3.1 trillion annually, which is about 20% of their revenue. It doesn’t stop there. Poor data quality reduces labor productivity by up to 20% and wastes 21 cents of every marketing dollar. These numbers highlight how critical it is to track and maintain data lineage. Without it, organizations face failed projects, wasted resources, and missed opportunities.Amplification of AI BiasBias in AI systems is a hot topic, and for good reason. When data lineage is overlooked, it becomes nearly impossible to trace the origins of training data. This lack of visibility allows biases to slip through unnoticed. I’ve learned that lineage tracking is essential for identifying and addressing these biases.Here’s how it works:* It helps track datasets used in model development, making it easier to spot biases.* During deployment, it allows tracing inputs and outputs, so decisions can be linked to specific data sources.* It ensures the provenance and quality of training data, which is critical for ethical AI practices.Without lineage, biases can amplify over time, leading to unfair or harmful outcomes. This isn’t just a technical issue—it’s an ethical one.Increased Risk of Regulatory ViolationsRegulations like GDPR and the EU AI Act demand transparency in data handling. Ignoring data lineage puts organizations at risk of non-compliance. I’ve seen how missing or incorrect lineage can lead to misguided decisions and hefty fines. For instance, financial institutions must trace risk model outputs to comply with standards like BCBS 239. Without proper lineage, they risk violating these regulations.Organizations also face reputational damage when they fail to demonstrate compliance. Privacy laws require clear documentation of data handling processes. Missing lineage exposes companies to penalties and erodes trust with stakeholders.Tip: Think of data lineage as your safety net. It not only ensures compliance but also protects your organization from operational failures and legal risks.Neglecting

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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:163618581Thu, 15 May 2025 09:21:25 +0000Mirko PetersImagine pouring millions into building an AI system, only to watch it crumble because of something as fundamental as data lineage. It happens more often than you’d think. Poor data quality is the silent culprit behind 87% of AI projects that never...Data lineage is like a map that shows the journey of your data from its origin to its final destination. It’s not just about where the data comes from but also how it transforms along the way. Think of it as a detailed record of every stop your data makes, every change it undergoes, and every system it passes through.Here’s a quick breakdown to make it clearer:Why does this matter? Without understanding data lineage, you’re flying blind. You can’t ensure transparency, improve data quality, or meet compliance standards.Key Components of Data LineageNow, let’s talk about what makes up data lineage. It’s not just one thing—it’s a combination of several elements working together.* IT systems: These are the platforms where data gets transformed and integrated.* Business processes: Activities like data processing often reference related applications.* Data elements: These are the building blocks of lineage, defined at conceptual, logical, and physical levels.* Data checks and controls: These ensure data integrity, as outlined by industry standards.* Legislative requirements: Regulations like GDPR demand proper data processing and reporting.* Metadata: This describes everything else about the data, helping us understand its lineage better.When all these components come together, they create a framework that ensures your data is reliable, traceable, and compliant.The Role of AI-Powered Data LineageHere’s where things get exciting. AI-powered data lineage takes traditional lineage tracking to the next level. It uses automation to map out data transformations across complex systems, including multi-cloud environments.Imagine trying to track data manually across dozens of platforms—it’s nearly impossible. AI-powered systems handle this effortlessly, improving governance, compliance, and operational efficiency. Automated lineage tracking doesn’t just save time; it also boosts transparency and reliability.Organizations using AI-powered data lineage report fewer errors and better decision-making. It’s a game-changer for anyone dealing with large-scale data operations.Why AI Developers Should Prioritize Data LineageEnsuring Transparency and AccountabilityWhen it comes to building trust in AI, transparency and accountability are non-negotiable. As an AI developer, I’ve seen how data lineage plays a pivotal role in achieving both. It’s like having a detailed map that shows every twist and turn your data takes. This map ensures that every decision made by your AI system can be traced back to its source.Here’s why this matters. Imagine...]]>5905falsefullhttps://www.spreaker.com/episode/how-ai-creates-brand-brains-that-outperform-teams--68938301
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:163192846Fri, 09 May 2025 08:07:33 +0000Mirko PetersLet’s start with a confession: The first time you crack open ChatGPT to churn out a week of social posts, it’s a little like biting into what you thought was a gourmet burger, only to find it’s all bun, no flavor. I’ve been there. Fresh off another...5394falsefullhttps://www.spreaker.com/episode/the-business-leaders-guide-to-ai-aha-moments--68938297
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:163122582Thu, 08 May 2025 10:52:54 +0000Mirko PetersA few years ago, I spent an entire week buried in a windowless conference room, wrestling quarterly data into something our CEO wouldn't immediately toss in the recycling bin. By Friday afternoon, my mind felt like overcooked spaghetti. Had you told...5533falsefullhttps://www.spreaker.com/episode/what-a-user-centric-data-map-looks-like--68938310
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:163050262Wed, 07 May 2025 13:00:49 +0000Mirko PetersHave you ever watched a symphony orchestra perform? The seamless blend of various instruments guided by a conductor can leave you awe-inspired. Interestingly, I’ve come to realize that synchronizing a data team carries similarities to this orchestral...5130falsefullhttps://www.spreaker.com/episode/why-your-data-might-be-lying-to-you--68938305
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162966004Tue, 06 May 2025 11:46:54 +0000Mirko PetersLate one night, as I stared at my screen, I couldn’t shake the nagging feeling that my forecasting model was sabotaged by something much deeper than my code. The fatigue of endless hours of tweaking parameters was overwhelming, yet I knew the glitch...5344falsefullhttps://www.spreaker.com/episode/true-data-detective-how-data-stewards-turn-chaos-into-clarity--68938299
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162872712Mon, 05 May 2025 11:08:38 +0000Mirko PetersAs I reflect on my journey through the realm of data management, I can't help but marvel at the pivotal role played by data stewards. These unsung heroes often work behind the scenes to ensure data integrity and prevent costly mistakes. Take, for...5543falsefullhttps://www.spreaker.com/episode/the-data-silo-escape-room-how-federated-governance-unlocks-data-agility--68938306
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162742274Sat, 03 May 2025 06:10:00 +0000Mirko PetersImagine being trapped in a room with your colleagues, each holding crucial pieces of information needed to solve a puzzle, but there are locked doors preventing you from sharing data. This scenario of a data silo escape room encapsulates the...5153falsefullhttps://www.spreaker.com/episode/transform-your-career-with-the-seven-rings-of-data-leadership--68938309
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162678204Fri, 02 May 2025 08:52:28 +0000Mirko PetersImagine pitching your data findings to a room full of executives, not met with polite nods but with an eagerness to reshape strategy based on your insights. This is the transformative power of data leadership. Despite the billions spent on data...5086falsefullhttps://www.spreaker.com/episode/transforming-data-science-strategies-from-plans-to-behavioral-commitments--68938311
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162518216Wed, 30 Apr 2025 07:08:04 +0000Mirko PetersWhile navigating the intricate world of data science, I’ve encountered countless misguided attempts at formulating strategies. The realization struck me that many organizations often mistake detailed plans for effective strategies. I remember a...5202falsefullhttps://www.spreaker.com/episode/openai-s-foray-into-social-networking-a-strategic-move-or-a-detour--68938312
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162308958Mon, 28 Apr 2025 06:55:08 +0000Mirko PetersWhen I first heard that OpenAI was developing a social network akin to Twitter, I was caught off guard. A company renowned for its AI chatbots like ChatGPT diving into social media? It sparked an array of thoughts and questions. Upon deeper...4970falsefullhttps://www.spreaker.com/episode/unlocking-the-value-of-iot-data-transformations-from-raw-to-refined--68938315
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162197014Sat, 26 Apr 2025 14:35:57 +0000Mirko PetersAs I sat in a meeting recently, a colleague shared a fascinating statistic that left me awestruck: the average car today boasts around 200 sensors, generating data in approximately 195 formats. It's incredible to think that our daily lives are now...5037falsefullhttps://www.spreaker.com/episode/machine-learning-the-hidden-patterns-in-your-data--68938313
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162084940Fri, 25 Apr 2025 07:04:38 +0000Mirko PetersAs I sift through the mountain of data my business generates daily, I often find myself asking: How can I truly harness this information to guide my decisions? It wasn't until I delved into machine learning that I realized the hidden goldmine of...5098falsefullhttps://www.spreaker.com/episode/dashboards-vs-data-stories-choose-wisely--68938316
Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:162001070Thu, 24 Apr 2025 06:26:56 +0000Mirko PetersHave you ever poured your heart into a dazzling dashboard, only to find it gathering dust in a corner of the executive suite? I have—and it sparked my curiosity about what makes data truly compelling for decision-makers. This realization kicked off my...5366falsefullhttps://www.spreaker.com/episode/mastering-the-art-of-dashboard-design-transforming-data-into-actionable-insights--68938304
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:161887041Wed, 23 Apr 2025 06:38:41 +0000Mirko PetersDuring my journey into the world of data visualization, I was struck by how often well-intentioned dashboards miss the mark. One day, while reviewing various dashboards created for a retail chain, I found myself wondering: why do some dashboards...5324falsefullhttps://www.spreaker.com/episode/navigating-the-statistical-seas-five-pillars-of-effective-data-analysis--68938314
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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.]]>substack:post:161861388Tue, 22 Apr 2025 09:24:45 +0000Mirko PetersThroughout my early journey in data science, I often felt overwhelmed by the multitude of statistical techniques at my fingertips. It wasn’t until a mentor introduced me to five guiding principles that I began to make sense of the chaos. These...5552falsefull