Synchronizing big data: 5 ways to ensure big data accuracy

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Earlier this year, I was shopping for a specific closet door at a home improvement store, and the store said it still had three such doors in stock. I drove to the store, and although the store’s inventory reported on the associate’s mobile device that three such units were in stock—the reality was that not only were the doors not in stock at the store, but they had actually been discontinued.

I’m sure I’m not the only consumer who has been frustrated by the “stockout” problem. Stockouts are an all too common occurrence across many industries and have been exacerbated as companies struggle with synchronizing the data from the many disparate systems they run, including systems that house big data. When data flowing in from these systems is not adequately synchronized with what is going on in the real world, customers can be disappointed and management risks making decisions based upon data that isn’t fact.

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