How big data brings BI, predictive analytics together

By Allen Bernard, CIO |  Big Data, Analytics

For as long as anyone can remember, the world of predictive analytics has been the exclusive realm of ivory-tower statisticians and data scientists who sit far away from the everyday line of business decision maker. Big data is about to change that.

As more data streams come online and are integrated into existing BI, CRM, ERP and other mission-critical business systems, the ever-elusive (and oh so profitable) single view of the customer may finally come into focus. While most customer service and field sales representatives have yet to feel the impact, companies such as IBM and MicroStrategy are working to see that they do soon.

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Imagine a world in which a CSR sitting at her console can make an independent decision on whether a problem customer is worth keeping or upgrading. Imagine, too, that a field salesman can change a retailer's wine rack on the fly based on the preferences that partiers attending the jazz festival next weekend have contributed on Facebook and Twitter.

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Big data is pushing a tool more commonly used for cohort and regression analysis into the hands of line-level managers, who can then use non-transactional data to make strategic, long-term business decisions about, for example, what to put on store shelves and when to put it there.

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However, big data is not about to supplant traditional BI tools, says Rita Sallam, Gartner's BI analyst. If anything, big data will make BI more valuable and useful to the business. "We're always going to need to look at the past...and when you have big data, you are going to need to do that even more. BI doesn't go away. It gets enhanced by big data."

How else you will know if what you are seeing in the initial phases of discovery will indeed bear out over time. For example, do red purses really sell better than blue ones in the Midwest? An initial pass through the data may suggest so-more red purses sold last quarter than ever before, therefore, red purses sell better.


Originally published on CIO |  Click here to read the original story.
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