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Databricks Certified Data Analyst Associate Sample Questions:

1. A data analyst has set up a SQL query to run every four hours on a SQL endpoint, but the SQL endpoint is taking too long to start up with each run.
Which of the following changes can the data analyst make to reduce the start-up time for the endpoint while managing costs?

A) Turn off the Auto stop feature
B) Use a Serverless SQL endpoint
C) Reduce the SQL endpoint cluster size
D) Increase the SQL endpoint cluster size
E) Increase the minimum scaling value

2. A data analyst has been asked to configure an alert for a query that returns the income in the accounts_receivable table for a date range. The date range is configurable using a Date query parameter.
The Alert does not work.
Which of the following describes why the Alert does not work?

A) The wrong query parameter is being used. Alerts only work with drogdown list query parameters, not dates.
B) Queries that use query parameters cannot be used with Alerts.
C) The wrong query parameter is being used. Alerts only work with Date and Time query parameters.
D) Queries that return results based on dates cannot be used with Alerts.
E) Alerts don't work with queries that access tables.

3. A data engineering team has created a Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables. The microbatches are triggered every minute.
A data analyst has created a dashboard based on this gold-level data. The project stakeholders want to see the results in the dashboard updated within one minute or less of new data becoming available within the gold-level tables.
Which of the following cautions should the data analyst share prior to setting up the dashboard to complete this task?

A) The gold-level tables are not appropriately clean for business reporting
B) The streaming cluster is not fault tolerant
C) The dashboard cannot be refreshed that quickly
D) The required compute resources could be costly
E) The streaming data is not an appropriate data source for a dashboard

4. Delta Lake stores table data as a series of data files, but it also stores a lot of other information.
Which of the following is stored alongside data files when using Delta Lake?

A) None of these
B) Owner account information
C) Table metadata
D) Table metadata, data summary visualizations, and owner account information
E) Data summary visualizations

5. Consider the following two statements:
Statement 1:

Statement 2:

Which of the following describes how the result sets will differ for each statement when they are run in Databricks SQL?

A) When the first statement is run, all rows from the customers table will be returned and only the customer_id from the orders table will be returned. When the second statement is run, only those rows in the customers table that do not have at least one match with the orders table on customer_id will be returned.
B) There is no difference between the result sets for both statements.
C) The first statement will return all data from the customers table and matching data from the orders table. The second statement will return all data from the orders table and matching data from the customers table. Any missing data will be filled in with NULL.
D) When the first statement is run, only rows from the customers table that have at least one match with the orders table on customer_id will be returned. When the second statement is run, only those rows in the customers table that do not have at least one match with the orders table on customer_id will be returned.
E) Both statements will fail because Databricks SQL does not support those join types.

Solutions:

Question # 1 Answer: B

Question # 2 Answer: B

Question # 3 Answer: D

Question # 4 Answer: C

Question # 5 Answer: D