Are You a Bystander to Bad Data? by Jim Harris.
From the post:
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.
“At a minimum,” Redman explained, “others using the erred data may not spot the error. 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.
“And failure to provide feedback,” Redman continued, “is but the proximate cause. The deeper root issue is misplaced accountability — or failure to recognize that accountability for data is needed at all. People and departments must continue to seek out and correct errors. They must also provide feedback and communicate requirements to their data sources.”
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.
[I removed two incorrect links in the quoted portion of Jim’s article. Were pointers to the rapper “Redman” and not Tom Redman. And I posted a comment on Jim’s blog about the error.]
Take the time to think about providing feedback on bad data.
Would bad data get corrected more often if correction was easier?
What if a data stream could be intercepted and corrected? Would that make correction easier?