![]() I definitely agree with Redman and Jones about the need for feedback loops, but I have found, more often than not, that no feedback at all is provided on data quality issues because of the assumption that data quality is someone else’s responsibility. In his blog post The Secret to an Effective Data Quality Feedback Loop, Dylan Jones responded to Redman’s blog post with some excellent insights regarding data quality feedback loops and how they can help improve your data quality initiatives. They must also provide feedback and communicate requirements to their data sources.” ![]() People and departments must continue to seek out and correct errors. The deeper root issue is misplaced accountability - or failure to recognize that accountability for data is needed at all. “And failure to provide feedback,” Redman continued, “is but the proximate cause. There is no telling where it might turn up or who might be victimized.” And correcting bad data without providing feedback to its source also denies the organization an opportunity to get to the bottom of the problem. “At a minimum,” Redman explained, “others using the erred data may not spot the error. ![]() In his recent Harvard Business Review blog post Break the Bad Data Habit, Tom Redman cautioned against correcting data quality issues without providing feedback to where the data originated. ![]()
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