Has anyone else faced challenges with data integrity, especially when it comes to metrics that the C-suite relies on? I've noticed that user input often leads to these pesky data entry errors, and while we have audit tracking mechanisms in place to automate some reports, there are still critical issues that can result in misleading reports. Some departments refuse to conduct key audits that directly affect revenue and billing accuracy. I was thinking of implementing "assertions" in SQL queries to alert users when a report can't run due to data entry errors and show relevant rows from audit reports. However, the billing admin is against this, and the C-suite wants to avoid any obstacles to their revenue projections while refusing to hold anyone accountable. Is there a better approach that I might be missing? Any suggestions based on your experiences?
3 Answers
Honestly, the integrity concern here seems to stem more from data entry accuracy rather than tampering or manipulation. If you’re delivering what management requests, that should cover you. As for those departments not conducting audits, that's on them for not having reliable inputs to work with—it's more of a process issue than a data integrity one.
This isn’t really about data integrity as much as it is about the process of data collection and management. You could factor in some basic checks to flag major errors, but if they rely on manual entry, it’s likely they’re leaving themselves open to mistakes—something management should manage internally. It's up to them to keep that in check.
Thanks for the insight! I guess it is important to focus on the bigger picture and the processes involved.
It sounds like this isn't just an IT issue—it’s more about who provides the data. Sure, you can add checks to catch some obvious data entry errors, but if the departments aren't doing their part in auditing, it's a bigger problem with their willingness to give accurate data. Talk to your C-suite about the root cause instead of just throwing tech solutions at it.
Exactly! If they need certain metrics, they really should work with those teams to ensure the data's accurate. Otherwise, the reporting is just going to be flawed.
I totally agree with you! They have to take responsibility for their data quality. Automating reports won’t help if the numbers are made up.