Testing
Apache Iceberg tables support schema evolution, partition spec changes, time-travel queries, and row-level deletes — all of which are correctness-critical operations that are easy to break silently. This guide covers testing each of these operations using PyIceberg and a local catalog, verifying that column additions don't
Testing
Testing Redshift pipelines is expensive and slow when done against a live cluster. This guide covers running Redshift-compatible tests against LocalStack, validating COPY/UNLOAD workflows, asserting on distribution and sort key behavior, and integrating Great Expectations for ongoing data quality monitoring — all in a CI pipeline that costs nothing
Testing
BigQuery pipelines are notoriously hard to test because every query costs money and requires live infrastructure. This guide covers three layers of testing: bq-test-kit for Python unit tests against a local emulator, dbt's built-in test framework for data quality assertions, and direct SQL testing patterns
Security
SQLMap is the standard tool for automated SQL injection detection and exploitation. It supports every major injection technique, handles authentication, works with WAFs via tamper scripts, and integrates into CI pipelines. This guide covers practical testing workflows for development and security teams. What SQLMap Tests SQLMap detects and exploits SQL
Data Engineering
dbt's testing model goes well beyond the four built-in tests. Generic tests written as macros are reusable across your entire project, singular tests handle complex multi-table business rules, and the dbt-expectations package brings 50+ Great Expectations-style assertions into SQL. In CI, dbt test --select