I concur with @SASKiwi ... You can easily set up a SAS Visual Analytics Data Quality Dashboard that acts as a "command center" to provide a bird's-eye view of data health, featuring quality-metrics, trend analysis, and drill-down capabilities for troubleshooting.
SAS Information Catalog is another tool you can use to monitor your data (and other) assets ... it provides a Column Analysis tab that automatically displays data quality metrics, allowing users to quickly identify potential issues, such as missing values, outliers and/or unexpected data types.
In short, you can track down data quality issues in the monthly feeds of data with SAS Viya by using a combination of automated data profiling, visual exploration, and intelligent monitoring tools to identify, analyze, and resolve data issues before they affect downstream analytics.
You can even carry out a statistical analysis to check whether there are any structural breaks between the old data (already in the system) and the new data (in the new monthly feed). Such breaks aren’t necessarily an error, of course, but you’ll want to be aware of them.
Good luck,
Koen
