Be able to pick the right Databricks SQL command for a stated data-management goal: OPTIMIZE for small-file compaction, DESCRIBE HISTORY for audits, and correct DROP TABLE expectations. The most important thing is knowing that managed Unity Catalog tables lose their data when dropped.
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Domain overview
This domain covers how Databricks analysts create, secure, and maintain data objects in Unity Catalog and the lakehouse. Questions present realistic scenarios about Delta table maintenance, DROP TABLE semantics, row-level security, and audit history, then ask you to choose the correct SQL command or Databricks feature that satisfies the requirement.
Exam objectives
Using OPTIMIZE and related Delta maintenance commands to compact small files for read performance
Understanding DROP TABLE behavior for managed versus external tables in Unity Catalog
Applying row-level security with dynamic views or row filter functions for territory-based access
Querying Delta table history with DESCRIBE HISTORY to audit operations, users, and timestamps
Assuming DROP TABLE only removes metadata; for managed Unity Catalog tables it also deletes the underlying data files
Confusing table access control with row-level filtering; GRANT SELECT alone cannot restrict rows by region
Using VACUUM or OPTIMIZE without understanding retention, file compaction, and when each maintenance command applies
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A data engineer has created a Delta table named `sales_summary` and needs to ensure that downstream analysts can only read rows where the `region` column matches their assigned territory. Which Databricks feature should be implemented to enforce this restriction securely at the row level?
2You are a data analyst working in Databricks SQL. Your workspace has Unity Catalog enabled. You need to inspect the metadata of a table named `customers` in the `sales` schema of the `retail` catalog, but you do not want to return any rows of data. Which SQL statement should you use?
3A data analyst has a Delta table `events` in Unity Catalog and needs to see the history of operations performed on it, including which user ran each operation and when, in order to audit recent changes. Which command should the analyst run?
4You are an analyst in a Unity Catalog-enabled Databricks workspace. A colleague has shared a table `finance.transactions` with you, and you need to confirm what privileges you currently hold on it before running a sensitive query. Which TWO of the following statements about inspecting privileges in Unity Catalog are accurate? (Choose two.)
5An analyst needs to create a new table in a Unity Catalog schema to store aggregated results, and the table should be managed by Unity Catalog so that storage lifecycle and access are handled by the platform. Which SQL statement correctly creates a managed Delta table named `summary` in the `analytics` schema of the `reporting` catalog?
6A data analyst runs the following command in a Databricks SQL editor connected to a Unity Catalog workspace: ```sql DROP TABLE IF EXISTS analytics.events.raw_clicks; ``` What is the result of this statement if `analytics.events.raw_clicks` is a managed Delta table?
7A data analyst runs `DROP TABLE IF EXISTS main.default.customer_orders;` in a Databricks SQL warehouse. The table is a managed Delta table in Unity Catalog and the analyst's identity has no applicable owner or admin privileges. What happens?
8A data analyst runs the following SQL in a Databricks SQL warehouse: CREATE OR REPLACE TEMPORARY VIEW monthly_sales AS SELECT month, SUM(revenue) AS total_revenue FROM sales.orders GROUP BY month; Immediately afterward, the analyst opens a new query tab in the same SQL warehouse session and runs SELECT * FROM monthly_sales; The query fails with a TABLE_OR_VIEW_NOT_FOUND error. What is the most likely reason for the failure?
9An analyst wants to create a view named `main.sales.high_value` that returns only rows from `main.sales.orders` where `total_amount > 1000`, and wants the view to reflect future updates to the base table automatically. Which statement should the analyst run?
10A data analyst has a Delta table silver.customers in Unity Catalog. A new privacy requirement states that analysts must never see the raw email column, but they still need to query all other columns. The analyst has CREATE VIEW and SELECT privileges on the schema. Which approach best enforces the requirement while keeping the table queryable?
11An analyst has a Delta table `bronze.raw_events` that has accumulated many small files over months of streaming writes. They now need to optimize read performance for downstream dashboards. Which Databricks SQL command should they run?
12A data analyst manages a Delta table gold.orders that is updated by an upstream job every 15 minutes. Analysts run long-running dashboard queries against the table and occasionally see stale results, even seconds after an update. The analyst wants dashboard queries to reflect the latest committed data without restarting the SQL warehouse. Which action should the analyst take?
13An analyst queries a view `main.ops.active_shipments` and receives a row-level filtered result, but the view's definition does not contain a WHERE clause. The analyst has SELECT on the view and on the base table. What most likely explains the filtered output?
14A data analyst queries a partitioned Delta table `logs.events` that has a `event_date` column. The query filters `WHERE event_date = '2024-06-01'`. Performance is poor even though the table is partitioned on `event_date`. Which factor most likely explains the poor performance?
15A data analyst is preparing a Delta table in Unity Catalog for a dashboard that must return results quickly and consistently. The analyst needs to reduce the number of small files and improve data skipping on a frequently filtered column. (Choose two.)
16An analyst has a CSV file at `abfss://raw@storage.dfs.core.windows.net/exports/2024_orders.csv` and wants to query it directly from Databricks SQL without loading it into a Delta table. Which approach is appropriate?
17A data analyst needs to create a new table that stores only aggregated daily sales totals derived from an existing Unity Catalog table, and the result must be refreshed nightly. They want the simplest object that persists the results and can be queried by other analysts. Which approach should they use?
Be able to pick the right Databricks SQL command for a stated data-management goal: OPTIMIZE for small-file compaction, DESCRIBE HISTORY for audits, and correct DROP TABLE expectations. The most important thing is knowing that managed Unity Catalog tables lose their data when dropped.
The Courseiva Databricks-DA-Assoc question bank contains 17 questions in the Managing Data domain. Click any question to see the full explanation and answer breakdown.
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