Inspect master data
Reporting Data Quality focuses on reporting data quality, locating missing fields, pruning stale reports, and enforcing trust rules. In AWRA, reporting turns raw transaction data into business intelligence and verified insights.
The primary objective is database transparency and decision support. Reporting teams should build dashboards that present reality without noise.
In practice, a data architect runs quality checks, flags items with missing categories, and prunes duplicate records.
Data quality audit path
Scan
Run data validation scan on item and client databases.
Flag
Identify missing fields, duplicates, or format errors.
Resolve
Update records using templates or prune duplicate lines.
Lock
Enforce input validation rules to prevent future errors.
Reporting model
- Dashboards should consolidate core metrics without clutter.
- Data fields require governance to protect user privacy.
- Exports and scheduled runs need monitoring and audit trails.
- Always verify report logic before publishing new index layouts.