Use cases

Use the cards below to explore different use cases that you can drive using Lakehouse, including sample queries.

Core metadata

✅

Metadata completeness tracking

Govern

Make sure assets are enriched with descriptions, owners, tags, certifications, and custom metadata, so they're discoverable and useful for data analysts.

🔁

Metadata export

Integrate

Export rich metadata for AI assistants, internal data marketplaces, and reverse sync back to Snowflake.

Lineage

🧬

Lineage analysis

Explore

Run base lineage queries with common filters for impact analysis, root cause investigations, and domain-specific lineage views.

📤

Lineage full export

Reuse

Export an enriched view of lineage that joins start and related assets, and reuse it across multiple lineage-driven queries.

📉

Downstream impacted dashboards

Notify

Find all downstream BI dashboards impacted by changes to a source table or view so you can notify owners and plan testing.

📌

Lineage impact analysis

Assess

Identify all downstream consumers of a table or column before making schema changes, deprecations, or migrations.

🕵️‍♀️

Lineage root cause analysis

Diagnose

Trace upstream from problematic dashboards or tables through transformations and source systems to pinpoint data issues.

🏷️

Lineage tags coverage across systems

Comply

Measure how governance tags such as PII and Confidential propagate across lineage and identify where coverage drops.

Glossary

📚

Glossary export and analysis

Document

Export glossary terms with glossaries, categories, and assigned assets to support documentation, compliance, and data governance review.