Audit Data Quality → Generate Governance Report → Track Compliance
Automatically assess your data's AI-readiness by scanning for quality issues, generating compliance reports, and tracking improvements over time.
Workflow Steps
Great Expectations
Run comprehensive data quality checks
Set up automated expectations for your datasets: completeness checks, value ranges, data types, uniqueness constraints, and referential integrity. Schedule these checks to run daily or after each data update.
Great Expectations
Generate data quality documentation
Create data docs that automatically document your data quality results, failed expectations, and trends over time. Include data lineage and schema information for audit trails.
Tableau
Build executive data quality dashboard
Connect Tableau to Great Expectations results. Create visualizations showing data quality scores by dataset, trending quality metrics, and AI-readiness indicators. Include alerts for critical quality failures.
Slack
Send automated quality alerts
Configure Slack notifications when data quality drops below thresholds. Include links to the detailed Tableau dashboard and specific Great Expectations reports for quick troubleshooting.
Workflow Flow
Step 1
Great Expectations
Run comprehensive data quality checks
Step 2
Great Expectations
Generate data quality documentation
Step 3
Tableau
Build executive data quality dashboard
Step 4
Slack
Send automated quality alerts
Why This Works
Combines automated testing with visual reporting to give executives confidence in data quality while providing technical teams actionable insights for improvements.
Best For
Data teams preparing enterprise data for AI initiatives
Explore More Recipes by Tool
Comments
No comments yet. Be the first to share your thoughts!