Course overview
Learn to define, measure, and enforce data quality across batch and streaming systems. Design practical controls for schema, completeness, validity, uniqueness, freshness, and lineage.
Standalone unit guides
Every unit is designed to be followed independently: review the guide, complete the lessons in order, finish the practical lab, pass the checkpoint, and deliver the unit project.
1. Quality Foundations3 lessons
Lesson sequence
- Data quality dimensions and risk - Free preview
- Profiling datasets and detecting anomalies
- Defining service levels and ownership
2. Automated Validation3 lessons
Lesson sequence
- Schema and data contracts
- Validation suites with Great Expectations
- Testing transformations in CI pipelines
3. Quality in Production3 lessons
Lesson sequence
- Freshness, volume, and distribution monitoring
- Incident response and root-cause analysis
- Capstone: observable quality gate