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Using data quality initiatives to dig deep and find 'the truth'

Rachel Wheeler Archive

Numerous companies are finding themselves more reliant on customer data today than they were even a few short years ago. Gathering more information can help them across a wide range of internal operations, whether it's making smarter banking decisions or improving their approach to marketing and sales. It should come as no surprise, then, that business leaders are making it a priority to gather more knowledge and practice strong database management techniques to boot.

Unfortunately, though, companies often fall short in their quest to "find the truth" in data. According to InformationWeek, it's become "widely accepted" that between 50 and 80 percent of all data warehousing projects end in failure. The speculation is that while business leaders aim to use data for solving all of their problems, they often focus too much on the data itself and not enough on their overall goals and the process at hand.

Jonas Olsson, founder and CEO of data warehousing firm Graz, told the news source that he's becoming increasingly concerned about this trend.

"There is much to be excited about in data management, with an incredible amount of innovation around the idea of getting more out of data," Olsson stated. "But, when creating a forest, it can be distracting to focus on the trees. With that in mind, focusing too much on the data can endanger the whole data warehouse project."

It's possible that there's a disconnect between "quality" in data versus "the truth." Every company wants to have information in its coffers that's as accurate and useful as possible, but it's equally important to have a well thought-out process behind every analytical endeavor. Each company has its own standards for data quality, and those standards are based on unique business goals. In a business context, "the truth" is relative.

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