databricks-unity-catalog

To query Unity Catalog system tables for table lineage in Databricks, you run SQL commands against the `system.access.table_lineage` table. This allows you to select source and target table names to visualize relationships and understand how specific tables interact within your data lake.

Yes, you can manage file uploads and downloads directly within Databricks Unity Catalog volumes. This Skill provides volume operations capabilities that allow you to upload, download, and manage files within your Unity Catalog storage infrastructure.

The best way to monitor data quality and detect drift in a large-scale data lake is by performing data profiling through Unity Catalog. This Skill automates statistical analysis and drift detection to help you monitor data quality across your Databricks environment.

Yes, you need Databricks SQL capabilities to analyze audit logs and billing from system tables. This Skill requires both Unity Catalog and Databricks SQL to query metadata, compute resources, and billing information effectively.

Querying system tables helps with managing large-scale Databricks data lakes by providing direct access to lineage, audit logs, compute resources, and metadata. This allows administrators to monitor operations, track table interactions, and maintain data quality across the environment.