Documenting table and column definitions so data can be discovered
Unity Catalog lets you attach human-readable comments to catalogs, schemas, tables, and columns so that data is discoverable and self-documenting through Catalog Explorer and SQL. These descriptions can be created and maintained via SQL DDL, Catalog Explorer UI edits, or AI-generated suggestions, and they persist as object metadata that governs how users find and understand data.
1 · Learn the must-know
- Use COMMENT ON TABLE, COMMENT ON COLUMN, or inline COMMENT clauses in CREATE/ALTER TABLE statements to add or update descriptions via SQL.
- In Catalog Explorer, you can manually edit table and column descriptions, or use Databricks Assistant/AI-generated comments (based on schema and sample data) and then review and accept them before saving.
- Table and column comments are stored as metadata in Unity Catalog and are visible to any user with sufficient privileges (e.g., SELECT or BROWSE) on that object, supporting data discovery and governance.
- ALTER TABLE ... ALTER COLUMN ... COMMENT '...' is used to add or change a column comment without altering the column's data or type.
- Comments are preserved across normal table operations (like INSERT, UPDATE, schema evolution via ADD COLUMN) but must be explicitly reapplied if a table is dropped and recreated rather than altered.
- Consistent, accurate table and column descriptions are a governance best practice tested on the exam because they directly support search, lineage understanding, and self-service analytics in Unity Catalog.
2 · Check your understanding
A data engineer runs CREATE TABLE gold.customer_summary AS SELECT customer_id, region, lifetime_value FROM silver.customers. The silver.customers table already has descriptive comments on the customer_id and region columns used for data discovery. After the CTAS statement finishes, the engineer opens Catalog Explorer and finds that gold.customer_summary has no column comments at all. What explains this, and what should the engineer do?
What you have tried across DP-750's objectives, not a readiness score.
Set up and configure an Azure Databricks environment15-20% of the exam0 of 13 tried
Secure and govern Unity Catalog objects15-20% of the exam0 of 12 tried
Prepare and process data30-35% of the exam0 of 28 tried
Deploy and maintain data pipelines and workloads30-35% of the exam0 of 24 tried
3 · Keep going
Ready for more? Take a weighted mock or try free practice questions.