Across the board, from operations to finances to customer satisfaction, the wrong data -- old, incomplete, and inaccurate information -- sets business back. According to MIT, "The cost of bad data is an astonishing 15 percent to 25 percent of revenue for most companies." The differences between these errant data are important. Also important is understanding that, strictly speaking, there is no "bad data." "Bad" makes data subject to the interpretation of a value judgment. A better, more descriptive term would be "technical debt." This is when engineers begin to indiscriminately start to modify code and introduce new features. Over time, features are layered one on top of another and, if unchecked, teams sacrifice long-term efficiency via a durable, hard-won solution for the…
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