Hi Team,

We need to perform a data quality check between an legacy table and a newly migrated table generated by refactored code. Specifically, we want to validate:

Schema & Volumetrics: Total row counts, column counts, and column data type distributions (e.g., integer vs. string counts).

Aggregations & Hashes: Column-level aggregates (sum and average for numeric/decimal types) and overall table-level MD5 hashes.

Row-Level Integrity: Primary key-based row-level MD5 hash comparisons to detect individual discrepancies.

Although we currently use custom Python/PySpark scripts, is there an existing data reconciliation framework that can automate these checks and generate detailed mismatch reports for further analysis?