What is the primary purpose of Unity Catalog in the Databricks platform?

To build and deploy machine learning models.

To provide unified governance for data access, permissions, and metadata across workspaces.

To provide a storage format with ACID transactions.

To serve as a compute engine for running SQL queries.

A data team needs to build a pipeline that ingests raw JSON files from cloud storage, cleans and validates the data, and then writes the results to a Delta table for downstream analytics. They want the pipeline to automatically handle new files as they arrive, enforce data quality rules, and retry failed tasks. Which combination of Databricks components should they use?

Mosaic AI to train a model that cleans the data, and a Delta Live Table to store the output

Databricks SQL with a scheduled query and a dashboard to monitor data quality

Unity Catalog to define data quality rules and a Lakeflow Job to run the pipeline

Delta Live Tables with expectations and a Lakeflow Job to schedule and monitor the pipeline

An organization is evaluating Databricks to replace their existing data warehouse and data lake. They want a single platform where they can store all their data, run SQL queries, build dashboards, and manage access centrally. Which architecture best describes this?

Data lake with Delta Live Tables for querying and Lakeflow Jobs for governance

Lakehouse architecture with Delta Lake for storage, Databricks SQL for querying, and Unity Catalog for governance

Separate systems: one for storage, one for SQL, and one for governance

Data warehouse with Mosaic AI for storage and Databricks SQL for querying

Which of the following is a capability of Databricks SQL?

Enforcing column-level access controls.

Creating and sharing interactive dashboards.

Defining data quality expectations on pipelines.

Managing model versions and deployments.

Which of the following is a feature of Lakeflow Jobs?

Declarative data quality checks on streaming data.

Enforcement of column-level access controls.

Automatic retry of failed tasks to improve reliability.

Model versioning and deployment to endpoints.

DatabricksCertified Data Analyst Associate

Domain 1Objective 1

Describe the Core Components of the Databricks Intelligence Platform, Including Mosaic AI, DeltaLive Tables, Lakeflow Jobs, Data Intelligence Engine, Delta Lake, Unity Catalog, and Databricks SQL. DATA-ANALYST-ASSOCIATE Practice Questions (Page 1)

Part of the Section 1: Understanding of Databricks Data Intelligence Platform domain, which makes up ~12% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~4–7 in this domain), expect 1–2 from this objective — we provide 34 practice questions to prepare you well beyond it. (estimate)

34questions here

7free pages

8concepts

Questions 1–5

1foundation · easy
What is the primary purpose of Unity Catalog in the Databricks platform?
Select an answer first
2application · medium
A data team needs to build a pipeline that ingests raw JSON files from cloud storage, cleans and validates the data, and then writes the results to a Delta table for downstream analytics. They want the pipeline to automatically handle new files as they arrive, enforce data quality rules, and retry failed tasks. Which combination of Databricks components should they use?
Select an answer first
3application · medium
An organization is evaluating Databricks to replace their existing data warehouse and data lake. They want a single platform where they can store all their data, run SQL queries, build dashboards, and manage access centrally. Which architecture best describes this?
Select an answer first
4foundation · easy
Which of the following is a capability of Databricks SQL?
Select an answer first
5foundation · easy
Which of the following is a feature of Lakeflow Jobs?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

Next 5 questions →Back to DATA-ANALYST-ASSOCIATE

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by Databricks. “DATA-ANALYST-ASSOCIATE” is a trademark of its owner, used for identification only.