Opinion: When is a hybrid approach right for the enterprise data warehouse?

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After attending a recent analytics conference sponsored by Gartner Inc., I walked away with both new and updated information, as well as a lingering, disquieting observation. In a nutshell – there is lots of data out there with more pouring in every day. Yet it’s really hard to derive insights from it.

As someone once said “We have oceans of data, yet only puddles of information.”

While this is not breaking news, this perception persists largely because the prevailing enterprise data warehouse (EDW) architecture is unable to meet new, rapidly emerging business requirements. That means many new business requirements are depending on data that, in the best case, is at least being stored, but certainly not explored.

Fortunately, radical measures like rip and replace are unwarranted, as the situation can be addressed by augmenting the EDW. Augmentation implies adding a big data component, that is, a big data warehouse, or BDW, to supplement the enterprise data warehouse.

Adding a big data element to the configuration creates a hybrid solution that is flexible, enduring, and affordable. In other words, the fix is not binary, as the solution needs both architectures operating in pursuit of the same business objectives – getting information into the hands of knowledge workers quickly and easily.

View the original article here, to read what broad scenarios are in use today by numerous enterprises, and all made possible by a hybrid solution.

Adam Lorant is the VP Product and Solutions and co-founder of PHEMI Systems, responsible for driving the the product vision and strategy. He works closely with leading healthcare research organizations, healthcare providers, and payer organizations to help them define and implement their big data strategies.


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