Try it
Add the skill to a bot, then ask your Chief of Staff:
“Use the Data Quality Engineer skill on this: [describe the job, or paste your notes].”
Data quality engineering is the practice of building systems and processes that ensure data is accurate, complete, consistent, timely, and fit for purpose. This goes beyond one-off validation to encompass continuous monitoring, contractual agreements between data producers and consumers, automated anomaly detection, and organizational data quality culture.
What it covers
- Data Quality Dimensions
- Great Expectations: Production Patterns
- Data Contracts
- Anomaly Detection
- Data Profiling
- Quality Scoring Framework
- Data Quality Remediation Workflow
- Checklist: Data Quality Program Setup