Fifty years after the expression "garbage in, garbage out" was coined, we still struggle with data quality. Studies show that knowledge workers waste a significant amount of time looking for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust. When data are unreliable, managers quickly lose faith in them and fall back on their intuition to make decisions, steer their companies, and implement strategy. They're also much more apt to reject important, counterintuitive implications that emerge from big data analyses. The good news is that improving data quality is often not as hard as you might think, the author asserts. The solution is not better technology: It's better communication between the creators of data and the data users; a focus on getting the process right going forward rather than on cleaning up existing bad data; and, above all, the shifting of responsibility for data quality away from IT folks, who don't own the business processes that create the data, and into the hands of managers, who are highly invested in getting the data right.

【書誌情報】

ページ数：6ページ

サイズ：A4

商品番号：HBSP-R1312E

発行日：2013/12/1

登録日：2013/12/10