Databricks Data Engineer Associate Certification Sample Questions

03. A data engineer is configuring Delta Sharing for a multi-team project where teams from different departments will need to access shared data. The data engineer has successfully created a Unity Catalog metastore and is now setting up the Delta Share.
The goal is to ensure that internal teams can access the data with full permissions, while external partners can only read the shared data. Which action should the Data Engineer take to configure the sharing?
a) Grant READ permissions to external partners through the Delta Share and READ/WRITE permissions to internal teams on Unity Catalog.
b) Create a Delta Share, add the internal team's tables and views, and assign READ/WRITE permissions to both external partners and internal teams.
c) Create a Delta Share, add the internal team's tables and views, and assign READ/WRITE permissions to both external partners and internal teams.
d) Create a Delta Share, set up a secure access URL for internal teams and external partners, and distribute the URL to provide them access to the shared data.

04. A data engineer is curating data in the silver layer of a hospital management data warehouse system. The data engineer is trying to aggregate hospital billing data from a table patient_billing to generate a daily revenue fact table daily_revenue.
Assume this as a sample of the dataframe billing_df:

Which code snippet aggregates the amount billed per day with the unique invoices from a Dataframe billing_df?
a) daily_revenue_df = billing_df.groupBy("billing_date").agg( sum("amount_billed").alias("total_revenue"), sum("billing_id").alias("total_invoices") )
b) daily_revenue_df = billing_df.groupBy("billing_date").agg( col("amount_billed").alias("total_revenue"), count("billing_id").alias("total_invoices") )
c) daily_revenue_df = billing_df.groupBy("billing_date").agg( sum("amount_billed").alias("total_revenue"), count_distinct("patient_id").alias("total_invoices") )
d) daily_revenue_df = billing_df.groupBy("billing_date").agg( sum("amount_billed").alias("total_revenue"), count_distinct("billing_id").alias("total_invoices") )

05. A data engineer has determined that a table of the following format is necessary:

Which code block is used by SQL DDL command to create an empty Delta table in the above format, regardless of whether a table already exists with this name?
a) CREATE OR REPLACE TABLE table_name WITH COLUMNS ( employeeId STRING, startDate DATE, avgRating FLOAT ) USING DELTA
b) CREATE TABLE IF NOT EXISTS table_name ( employeeId STRING, startDate DATE, avgRating FLOAT )
c) CREATE TABLE table_name AS SELECT employeeId STRING, startDate DATE, avgRating FLOAT
d) CREATE OR REPLACE TABLE table_name ( employeeId STRING, startDate DATE, avgRating FLOAT )

06. A new data engineering team team has been assigned to an ELT project. The new data engineering team will need full privileges on the table sales to fully manage the project. Which command can be used to grant full permissions on the database to the new data engineering team?
a) GRANT SELECT ON TABLE sales TO team;
b) GRANT USAGE ON TABLE sales TO team;
c) GRANT ALL PRIVILEGES ON TABLE sales TO team;
d) GRANT ALL PRIVILEGES ON TABLE team TO sales;

07. A data engineer is working on a Databricks project with a schema named sales_data that stores transactional sales information. The analyst group, responsible for analyzing this data, needs read-only access to the sales_data schema.
Which SQL command should the data engineer use to grant the analyst group read-only access to the sales_data schema, assuming that the analyst group already has USE CATALOG and USE SCHEMA permissions?
a) GRANT ALL PRIVILEGES ON SCHEMA sales_data TO analysts;
b) GRANT SELECT ON SCHEMA sales_data TO analysts;
c) GRANT INSERT ON SCHEMA sales_data TO analysts;
d) GRANT SELECT ON ALL TABLES IN SCHEMA sales_data TO analysts;

08. A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE. The table is configured to run in Development mode using the Continuous Pipeline Mode.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?
a) All datasets will be updated at set intervals until the pipeline is shut down.The compute resources will persist to allow for additional testing.
b) All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.
c) All datasets will be updated once and the pipeline will shut down.The compute resources will be terminated.
d) All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist until the pipeline is shut down.