Remove 2008 Remove Data Warehouse Remove Risk Remove Uncertainty
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Banking on mainframe-led digital transformation for financial services

IBM Big Data Hub

Banks have the most to gain if they succeed (and the most to lose if they fail) at bringing their mainframe application and data estates up to modern standards of cloud-like flexibility, agility and innovation to meet customer demand. Couldn’t execs have run better analyses to spot risks within the data?

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New Thinking, Old Thinking and a Fairytale

Peter James Thomas

A decade later, Gartner had some rather sobering thoughts to offer on the same subject: Gartner predicted that through 2008, about 60% of organizations that outsource customer-facing functions will see client defections and hidden costs that outweigh any potential cost savings. King was a wise King, but now he was gripped with uncertainty.

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Data Science, Past & Future

Domino Data Lab

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams.

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Cloudera + Hortonworks, from the Edge to AI

Cloudera

In 2008, I co-founded Cloudera with folks from Google, Facebook, and Yahoo to deliver a big data platform built on Hadoop to the enterprise market. We believed then, and we still believe today, that the rest of the world would need to capture, store, manage and analyze data at massive scale. Forward-Looking Statements.