Ensuring Data Quality
The task statement with the least obvious service answer, because quality is a design problem first. The failure modes that reach production, completeness and consistency and freshness as measurable things, Glue Data Quality and Deequ, where a quality gate belongs in the line, and what to do when bad data has already landed.
Content current as of 2026-10.
Lessons
- How data goes wrong in production
- Making quality measurable
- Glue Data Quality and Deequ
- Gates, quarantine, and backfill
Sources
- AWS Glue developer guide — AWS Glue Data Quality
- AWS Glue developer guide — DQDL rule type reference
- AWS Glue developer guide — DataFreshness rule type
- AWS Glue developer guide — getting started with AWS Glue Data Quality for the Data Catalog
- AWS Big Data Blog — write-audit-publish with Apache Iceberg branching and AWS Glue Data Quality