Governance, quality & lineage
Make data meaning, quality, policy and downstream impact visible throughout the platform.
Engineering scope
A catalog records ownership, classification and purpose for datasets and services. Quality, freshness and schema checks detect broken contracts or stale inputs before they quietly propagate into reports and applications. Sensitive-data discovery supports classification review rather than assuming detection is infallible.
Provenance and transformation lineage connect source records, pipelines, models and outputs. Impact analysis identifies consumers of a proposed change; a model and policy inventory records what is deployed, which version applies and who is accountable.
Masking, governed sharing and approval workflows apply the configured purpose, retention and deletion rules. Audit trails expose policy changes and data use to permitted reviewers; deletion processes address derived data and backups according to the agreed retention design.
Configured inputs
Catalog entries, owner assignments, classifications, quality contracts, lineage events, model/policy inventories and retention requirements.
Configured outputs
Quality reports, freshness alerts, lineage and impact views, masked products, sharing decisions and auditable policy/deletion records.
Roles & operational workflow
Stewards investigate quality failures; domain owners approve definitions and sharing; policy owners set purpose and retention; platform teams implement and demonstrate the controls.
Interfaces & governance
Checks and exceptions have named owners and escalation paths. Policy changes are reviewed and versioned; access to sensitive discovery findings is itself restricted. Audit evidence distinguishes configured control from tested enforcement.
Deployment implications
Catalog, scanners, quality execution and lineage storage can reside locally. Offline operations retain local policy and audit services; retention capacity and backup behaviour are established in architecture.
Deliverables & acceptance evidence
Acceptance includes deliberately failing quality/schema tests, source-to-output lineage, change impact, masking and denied sharing, retention/deletion exercises and audit retrieval with permitted identities.
Define the scope with a senior engineer.
Discuss your operating context, deployment environment and acceptance requirements with a senior engineer.
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