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Databricks Databricks-Certified-Data-Analyst-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Data-Analyst-Associate
Exam Name:
Databricks Certified Data Analyst Associate Exam
Certification:
Vendor:
Questions:
118
Last Updated:
Oct 5, 2026
Exam Status:
Stable
Databricks Databricks-Certified-Data-Analyst-Associate

Databricks-Certified-Data-Analyst-Associate: Data Analyst Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Data Analyst Associate Exam Questions and Answers

Question 1

The stakeholders.customers table has 15 columns and 3,000 rows of data. The following command is run:

After running SELECT * FROM stakeholders.eur_customers, 15 rows are returned. After the command executes completely, the user logs out of Databricks.

After logging back in two days later, what is the status of the stakeholders.eur_customers view?

Options:

A.

The view remains available and SELECT * FROM stakeholders.eur_customers will execute correctly.

B.

The view has been dropped.

C.

The view is not available in the metastore, but the underlying data can be accessed with SELECT * FROM delta. `stakeholders.eur_customers`.

D.

The view remains available but attempting to SELECT from it results in an empty result set because data in views are automatically deleted after logging out.

E.

The view has been converted into a table.

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Question 2

Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?

Options:

A.

( spark.readStream.load(rawSalesLocation) .writeStream .option( " checkpointLocation " , checkpointPath) .outputMode( " append " ) .table( " newSales " ))

B.

( spark.table( " sales " ) .withColumn( " avgPrice " , col( " sales " ) / col( " units " )) .writeStream .option( " checkpointLocation " , checkpointPath) .outputMode( " append " ) .table( " newSales " ))

C.

( spark.table( " sales " ) .withColumn( " avgPrice " , col( " sales " ) / col( " units " )) .writeStream .option( " checkpointLocation " , checkpointPath) .outputMode( " append " ) .table( " newSales " ))

D.

( spark.table( " sales " ) .filter(col( " units " ) > 0) .writeStream .option( " checkpointLocation " , checkpointPath) .outputMode( " append " ) .table( " newSales " ))

E.

( spark.table( " sales " ) .groupBy( " store " ) .agg(sum( " sales " )) .writeStream .option( " checkpointLocation " , checkpointPath) .outputMode( " complete " ) .table( " newSales " ))

F.

Option A

G.

Option B

Question 3

An analyst writes a query that contains a query parameter. They then add an area chart visualization to the query. While adding the area chart visualization to a dashboard, the analyst chooses " Dashboard Parameter " for the query parameter associated with the area chart.

Which of the following statements is true?

Options:

A.

The area chart will use whatever is selected in the Dashboard Parameter while all or the other visualizations will remain changed regardless of their parameter use.

B.

The area chart will use whatever is selected in the Dashboard Parameter along with all of the other visualizations in the dashboard that use the same parameter.

C.

The area chart will use whatever value is chosen on the dashboard at the time the area chart is added to the dashboard.

D.

The area chart will use whatever value is input by the analyst when the visualization is added to the dashboard. The parameter cannot be changed by the user afterwards.

E.

The area chart will convert to a Dashboard Parameter.