When regulatory requirements, data quality issues, or organisation scale demand a formal approach to knowing what data exists and who can access it.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: Databases & Data Engineering - Use case: Data Lineage & Governance Framework - Source task: - Build a data lineage and governance framework for {{describe_organisation_and_data_landscape}}. - Step 1: Lineage: define how to track data lineage (where data comes from, how it transforms, where it goes) : tool recommendation and implementation approach. - Step 2: Data Catalogue: design a data catalogue structure (datasets, owners, definitions, quality scores). - Step 3: Access Control: design data access policies by sensitivity tier (public, internal, confidential, restricted). - Step 4: Compliance: map compliance requirements (GDPR, HIPAA, or {{other}}) to governance controls. # Goal Lineage tracking design, data catalogue structure, access control policy, and compliance control mapping. # Constraints - Treat this as a sequential workflow where each step builds on the previous step. - Keep every step clearly labeled and easy to run separately if needed. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Lineage tracking design, data catalogue structure, access control policy, and compliance control mapping.
{{double-curly}} with your real context.When regulatory requirements, data quality issues, or organisation scale demand a formal approach to knowing what data exists and who can access it.
Start with a data catalogue even if you can't automate lineage yet — knowing what data exists and who owns it is more valuable than automated lineage with no ownership.
Debug this problem systematically. Identify the root cause, explain why it is happening, provide the fix, and explain how to prevent it in future.
Design the high-level architecture for this system. Cover components, data flow, scaling strategy, and key design decisions.
Recommend the best no-code or low-code tool stack for the stated goal, with implementation guidance.
Design the complete analysis approach for the stated question. Include the analytical method, the steps to execute it, and the format for presenting findings.