cloudthinker-ai Data Catalog Setup
Phase 1: Requirements & Tool Setup
- Define catalog requirements
- Automated metadata extraction from data sources
- Column-level lineage tracking
- Business glossary and term management
- Data quality scores integration
- Access request workflow
- Search and discovery interface
- API access for programmatic integration
- Classification and tagging support
- Configure catalog tool and integrations
- Set up authentication and access controls
Data Source Integration Plan
| Source | Type | Connector | Metadata Scope | Lineage | Priority |
|---|---|---|---|---|---|
| DB/Lake/Stream/API | Native/Custom | Schema/Stats/Quality | Yes/No | 1-5 |
Phase 2: Automated Metadata Extraction
- Configure metadata extraction
- Schema metadata (tables, columns, types)
- Usage statistics (query frequency, popular tables)
- Data freshness and update timestamps
- Column-level statistics (null rate, cardinality)
- Lineage from transformation tools (dbt, Spark, Airflow)
- Set extraction schedules (hourly, daily)
- Validate extracted metadata accuracy
- Handle schema evolution gracefully
Phase 3: Business Context Enrichment
- Add business context to technical metadata
- Business descriptions for tables and columns
- Business glossary terms and definitions
- Data domain classification
- Data sensitivity/classification labels
- Data owners and stewards
- Related documentation and wiki links
- Certified/endorsed dataset badges
- Prioritize enrichment for most-used datasets
- Assign enrichment owners per domain
Enrichment Progress
| Domain | Datasets | Descriptions | Owners Assigned | Classified | Certified | Progress |
|---|---|---|---|---|---|---|
| /total | /total | /total | /total | % |
Phase 4: Lineage & Impact Analysis
- Implement data lineage tracking
- Column-level lineage from ETL/ELT tools
- Dashboard-to-dataset lineage (BI tools)
- API-to-dataset lineage
- Cross-system lineage (operational DB to warehouse)
- Enable impact analysis
- Identify downstream consumers of any dataset
- Assess impact before schema changes
- Alert consumers of upstream changes
Phase 5: Access & Governance Integration
- Integrate access management
- Self-service data access requests
- Approval workflow for sensitive data
- Access audit trail
- Data classification drives access policies
- Time-bound access grants
- Integrate data quality metrics
- Link governance policies to catalog entries
Phase 6: Adoption & Training
- Drive catalog adoption
- Onboarding sessions for data consumers
- Integrate catalog into daily workflows (Slack, IDE)
- Measure adoption metrics (searches, views, contributions)
- Gamify contributions (leaderboard for documentation)
- Embed catalog links in BI tools and notebooks
- Track adoption metrics
Adoption Metrics
| Metric | Month 1 | Month 3 | Month 6 | Target |
|---|---|---|---|---|
| Weekly active users | > 50% of data users | |||
| Searches per week | ||||
| Datasets documented | % | % | % | > 80% |
| Access requests via catalog | > 90% |
Counter-Rationalizations
| Shortcut | Counter | Why |
|---|---|---|
| "We can skip some steps for this case" | Adapt the workflow steps, don't skip them | Skipped steps are where incidents and oversights originate |
| "The user seems to already know what to do" | Complete all workflow phases with the user | The workflow catches blind spots that experience alone misses |
| "This is a minor case, full process is overkill" | Scale the process down, don't turn it off | Minor cases become major when unstructured; the process scales, not disappears |
| "I'll fill in the details later" | Complete each section before moving on | Deferred details are forgotten; real-time capture is more accurate |
| "The template output isn't necessary" | Always produce the structured output format | Structured output enables comparison, audit trails, and handoff to other teams |
Output Format
- Integration Plan: Data sources and connector configuration
- Enrichment Guide: Standards for business metadata
- Lineage Map: Cross-system data lineage visualization
- Adoption Dashboard: Usage metrics and trends
- Governance Integration: Access policies and workflows
Action Items
- Configure catalog tool and data source connectors
- Run initial automated metadata extraction
- Enrich top 20% most-used datasets with business context
- Implement lineage tracking from transformation tools
- Set up access request workflow
- Conduct onboarding sessions for data teams
- Track adoption metrics monthly