As a Data Analyst, I use DataBuck to perform a validation of data before it is being used for reporting and analysis. Something that I find really powerful is the ability to perform source-to-target reconciliation for environments like GCP and Databricks.

Rather than just validating simple metrics like record counts or doing it manually, it helps to identify if there is a drift between the two and provides insight into what the drift is. This helps a lot when it comes to debugging if records were dropped somewhere down the line or an incorrect transformation happened.

I also find it helpful that it goes beyond just checking for nulls and format, and allows us to use business rules and context of data to validate and find issues relevant to our reporting use cases. Review collected by and hosted on G2.com.

Some of the advanced validation results could be made slightly more intuitive so that it is easier to understand what might be causing the issue Review collected by and hosted on G2.com.