You detect data anomalies regularly but business ignores them. What do you do?

< 1 min read

First, I would document the anomalies clearly, including when they occur and how they impact key metrics.
I would quantify the business impact so stakeholders understand the potential risk.
For example, incorrect data could lead to wrong decisions or inaccurate performance reporting.
Next, I would share specific examples where anomalies affected dashboard results.
In one project, duplicate records inflated sales numbers, which initially went unnoticed by the team.
Once we showed the difference in metrics before and after cleaning the data, stakeholders paid attention.
I would also suggest simple validation checks or alerts to detect these issues earlier.
If the problem continues, I would escalate it to the relevant data owners or managers.
Finally, I would continue monitoring the data and maintain clear documentation of recurring issues.

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