Ghost in the data

Healing Tables: When Day-by-Day Backfills Become a Slow-Motion Disaster

A data engineering team discovered that a three‑year SCD Type 2 backfill executed day‑by‑day produced 47,000 overlapping records, timeline gaps, and unrecoverable errors. The author introduced "Healing Tables," a framework that separates change detection from period construction and rebuilds the dimension in a single deterministic pass. The six‑step pipeline extracts effectivity points, generates time slices, joins multiple sources, computes hashes, compresses rows, and validates temporal integrity. This approach turns a fragile, incremental process into a fast, reproducible rebuild that can heal historical inconsistencies.