## Knowledge Catalog use cases

![](http://docs.cloud.google.com/static/dataplex/images/knowledge-catalog-concept.png) Explore hands-on tutorials and architectural guides across Knowledge Catalog (formerly Dataplex Universal Catalog). Learn how to ingest and enrich metadata, establish data governance, track comprehensive lineage, and ground AI agents with enterprise-ready data context. [Knowledge Catalog overview](http://docs.cloud.google.com/dataplex/docs/introduction) Aggregation Enrichment Search \& retrieval Data lineage Data governance Reference architecture Console Code \& API [Search \& retrieval Code \& API
Build an agent to discover data
Run complex, natural language queries on enterprise data assets, using a discovery agent that makes Knowledge Catalog API calls (Python).](https://docs.cloud.google.com/dataplex/docs/use-discovery-agent) [Enrichment Code \& API
Build an agent to enrich metadata
Generate AI-powered overviews for your data assets at scale, using an enrichment agent that makes Knowledge Catalog API calls (Python).](https://docs.cloud.google.com/dataplex/docs/build-agent-to-enrich-metadata) [Reference architecture Search \& retrieval
Implement agentic analytics workflows for distributed data
Architect cross-cloud analytics workflows across distributed data stores using AI agents and Knowledge Catalog as the context graph.](https://docs.cloud.google.com/architecture/agentic-ai-cross-cloud-analytics) [Enrichment Console
Establish foundational data context
Attach structured, schema-driven metadata (aspects) and business definitions (glossaries) to your data assets (entries) using the Google Cloud console.](https://docs.cloud.google.com/dataplex/docs/establish-foundational-data-context) [Data governance Search \& retrieval Code \& API
Enable policy-compliant lakehouse access with Knowledge Catalog
Create Apache Iceberg tables, enforce centralized data policies for column-level security, define security policies, and visualize automated data lineage.](https://docs.cloud.google.com/dataplex/docs/enable-policy-compliant-lakehouse-access) [Enrichment Console
Use discovery scan for structured data
Automatically ingest metadata from Google services like BigQuery.](https://docs.cloud.google.com/dataplex/docs/use-data-insights-structured-data) [Aggregation Console Code \& API
Manage entries and ingest custom sources
Index metadata from custom data sources using open APIs.](https://docs.cloud.google.com/dataplex/docs/ingest-custom-sources) [Enrichment Code \& API
Automatically profile data and ensure quality
Through Gemini CLI, use natural language queries to profile data and generate quality rules, then deploy data quality rules as automated scans.](https://docs.cloud.google.com/dataplex/docs/profile-ensure-data-quality) [Search \& retrieval Console
Use Gemini CLI to test data context
Verify that Knowledge Catalog can distinguish between source data and temporary derivatives, using natural language queries to Gemini CLI.](https://docs.cloud.google.com/dataplex/docs/use-gemini-cli-agent-to-test-data-context) [Data governance Data lineage Console
Analyze impact of data changes
Identify how data transformations affect downstream resources, data integrity, and workflows.](https://docs.cloud.google.com/dataplex/docs/lineage-use-cases-impact-analysis) [Data governance Data lineage Console
Analyze causes of a PII leak
Trace the flow of sensitive data back to the process that moves it from a trusted to an untrusted location.](https://docs.cloud.google.com/dataplex/docs/lineage-use-cases-pii-leakage) [Data governance Data lineage Console
Optimize storage costs
Reduce storage costs by identifying assets that are not actively used as sources for other processes.](https://docs.cloud.google.com/dataplex/docs/lineage-use-cases-cost-optimization) [Search \& retrieval Code \& API
Retrieve context for data assets
Retrieve pre-formatted, LLM-ready context for data assets using a single API request.](https://docs.cloud.google.com/dataplex/docs/retrieve-data-context)