11 docs tagged with "best-practices"

How to choose a lineage-generation mechanism, understand column-level and cross-system limits, run an impact analysis, report coverage honestly, and diagnose missing lineage.

Pick the simplest programmatic mechanism for a metadata task—API, SDK, packages, MDLH, or MCP—and design it to run safely at scale.

How to pick the simplest access-control mechanism, sequence a persona rollout, map SSO groups, and govern sensitive data without over-engineering.

Scope data products around use cases, model domains and ports correctly, govern publishing at scale, and pilot without over-engineering.

How to scope which assets to enrich, choose the right bulk mechanism, sequence enrichment so it grounds AI reliably, and answer the overwrite, quality, and security questions.

How to scope data quality to the assets that matter, choose and sequence rules, route alerts without creating noise, and position monitoring against pipeline tests.

How to choose an ingestion mechanism, scope a crawl, structure connections, and sequence a multi-connector rollout so lineage and trust land the first time.

Decide when to use MDLH, match your job to the right consumption pattern, and feed metadata to AI the way that stays accurate.

Best practices for querying and using the Gold namespace efficiently.

How to choose glossary structure, model metrics and KPIs as first-class terms, sequence rollout so the catalog actually gets populated, and ground the semantic layer for AI.

How to approach common platform decisions—bulk edits, enabling gated features, AI search, deletes—so you pick the right mechanism the first time and avoid the mistakes that stall rollouts.