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Free Databricks Databricks-Certified-Data-Analyst-Associate Exam Actual Questions

The questions for Databricks-Certified-Data-Analyst-Associate were last updated On Mar 28, 2025

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Question No. 1

A data team has been given a series of projects by a consultant that need to be implemented in the Databricks Lakehouse Platform.

Which of the following projects should be completed in Databricks SQL?

ATesting the quality of data as it is imported from a source

BTracking usage of feature variables for machine learning projects

CCombining two data sources into a single, comprehensive dataset

DSegmenting customers into like groups using a clustering algorithm

EAutomating complex notebook-based workflows with multiple tasks
Databricks SQL is a service that allows users to query data in the lakehouse using SQL and create visualizations and dashboards1.One of the common use cases for Databricks SQL is to combine data from different sources and formats into a single, comprehensive dataset that can be used for further analysis or reporting2.For example, a data analyst can use Databricks SQL to join data from a CSV file and a Parquet file, or from a Delta table and a JDBC table, and create a new table or view that contains the combined data3. This can help simplify the data management and governance, as well as improve the data quality and consistency.Reference:
Databricks SQL overview
Databricks SQL use cases
Joining data sources

Show Answer

Correct Answer: C

Question No. 2

How can a data analyst determine if query results were pulled from the cache?

AGo to the Query History tab and click on the text of the query. The slideout shows if the results came from the cache.

BGo to the Alerts tab and check the Cache Status alert.

CGo to the Queries tab and click on Cache Status. The status will be green if the results from the last run came from the cache.

DGo to the SQL Warehouse (formerly SQL Endpoints) tab and click on Cache. The Cache file will show the contents of the cache.

EGo to the Data tab and click Last Query. The details of the query will show if the results came from the cache.
Databricks SQL uses a query cache to store the results of queries that have been executed previously. This improves the performance and efficiency of repeated queries. To determine if a query result was pulled from the cache, you can go to the Query History tab in the Databricks SQL UI and click on the text of the query. A slideout will appear on the right side of the screen, showing the query details, including the cache status. If the result came from the cache, the cache status will show ''Cached''. If the result did not come from the cache, the cache status will show ''Not cached''. You can also see the cache hit ratio, which is the percentage of queries that were served from the cache.Reference: The answer can be verified from Databricks SQL documentation which provides information on how to use the query cache and how to check the cache status. Reference link: Databricks SQL - Query Cache

Show Answer

Correct Answer: A

Question No. 3

What is a benefit of using Databricks SQL for business intelligence (Bl) analytics projects instead of using third-party Bl tools?

AComputations, data, and analytical tools on the same platform

BAdvanced dashboarding capabilities

CSimultaneous multi-user support

DAutomated alerting systems
Databricks SQL offers a unified platform where computations, data storage, and analytical tools coexist seamlessly. This integration allows business intelligence (BI) analytics projects to be executed more efficiently, as users can perform data processing and analysis without the need to transfer data between disparate systems. By consolidating these components, Databricks SQL streamlines workflows, reduces latency, and enhances data governance. While third-party BI tools may offer advanced dashboarding capabilities, simultaneous multi-user support, and automated alerting systems, they often require integration with separate data processing platforms, which can introduce complexity and potential inefficiencies.

Show Answer

Correct Answer: A

Question No. 4

Which location can be used to determine the owner of a managed table?

AReview the Owner field in the table page using Catalog Explorer

BReview the Owner field in the database page using Data Explorer

CReview the Owner field in the schema page using Data Explorer

DReview the Owner field in the table page using the SQL Editor
In Databricks, to determine the owner of a managed table, you can utilize the Catalog Explorer feature. The steps are as follows:
Access Catalog Explorer:
In your Databricks workspace, click on the Catalog icon in the sidebar to open Catalog Explorer.
Navigate to the Table:
Within Catalog Explorer, browse through the catalog and schema to locate the specific managed table whose ownership you wish to verify.
View Table Details:
Click on the table name to open its details page.
Identify the Owner:
On the table's details page, review the Owner field, which displays the principal (user, service principal, or group) that owns the table.
This method provides a straightforward way to ascertain the ownership of managed tables within the Databricks environment. Understanding table ownership is essential for managing permissions and ensuring proper access control.

Show Answer

Correct Answer: A

Question No. 5

A data analyst is processing a complex aggregation on a table with zero null values and the query returns the following result: