The document discusses the challenges posed by 'data science gravity' on enterprise data management, tracing its historical context since 1968. It argues that traditional approaches to data scale poorly and introduces the concept of the predictive enterprise as a solution, emphasizing collaboration and built-in data science capabilities. The document advocates for a platform that enables scalability, elasticity, and agility through software as a service.

1. DATA HAS ALWAYS BEEN AN ENTERPRISE ASSET
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2. BUT “DATA SCIENCE GRAVITY”
IS PULLING YOU DOWN

3. SOME HISTORY
THE ENTERPRISE TEAM – CIRCA 1968
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4. NEXT GENERATION INTRODUCES “DATA”
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7. Pre-Hadoop, Pre-Internet Packages
DON’T scale economically
Code-led approaches
DON’T scale technically
Data-Scientists
DON’T scale physically
DATA SCIENCE’S LAWS OF GRAVITY
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8. THERE ARE WAYS TO DEFY
“DATA SCIENCE GRAVITY”
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9. THE PREDICTIVE ENTERPRISE IS THE ANSWER

10. IT NEEDS A FEW INGREDIENTS

11. A PLATFORM FOR COLLABORATION: 1+1 = 11

12. SERIOUS MATH THAT CAN EASILY SCALE

13. ELASTICITY, AGILITY AND SCALABILITY BUILT-IN

14. DATA SCIENCE ON TAP

15. SOFTWARE AS A SERVICE

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