How to Industrialize Data Science to Attain Mastery of Repeatable Intelligence Delivery
Dec 7, 2020 ·
30m 44s
Businesses these days are quick to declare their intention to become data-driven, yet the deployment of analytics and the use of data science remains spotty, isolated, and often uncoordinated. To...
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Businesses these days are quick to declare their intention to become data-driven, yet the deployment of analytics and the use of data science remains spotty, isolated, and often uncoordinated.
To fully reach their digital business transformation potential, businesses large and small need to make data science more of a repeatable assembly line -- an industrialization, if you will -- of end-to-end data exploitation.
The next BriefingsDirect Voice of Analytics Innovation discussion explores the latest methods, tools, and thinking around making data science an integral core function that both responds to business needs and scales to improve every aspect of productivity.
To learn more about the ways that data and analytics behave more like a factory -- and less like an Ivory Tower -- please welcome Doug Cackett, EMEA Field Chief Technology Officer at Hewlett Packard Enterprise. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Sponsor: Hewlett Packard Enterprise.]
show less
To fully reach their digital business transformation potential, businesses large and small need to make data science more of a repeatable assembly line -- an industrialization, if you will -- of end-to-end data exploitation.
The next BriefingsDirect Voice of Analytics Innovation discussion explores the latest methods, tools, and thinking around making data science an integral core function that both responds to business needs and scales to improve every aspect of productivity.
To learn more about the ways that data and analytics behave more like a factory -- and less like an Ivory Tower -- please welcome Doug Cackett, EMEA Field Chief Technology Officer at Hewlett Packard Enterprise. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Sponsor: Hewlett Packard Enterprise.]
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| Author | Dana Gardner |
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