Databricks DATABRICKS-CERTIFIED-DATA-ANALYST-ASSOCIATE Online Practice Questions and Exam Preparation

Databricks DATABRICKS-CERTIFIED-DATA-ANALYST-ASSOCIATE Online Questions & Answers

• Question 21:

  Which of the following describes how Databricks SQL should be used in relation to other business intelligence (BI) tools like Tableau, Power BI, and looker?

  A. As an exact substitute with the same level of functionality
  B. As a substitute with less functionality
  C. As a complete replacement with additional functionality
  D. As a complementary tool for professional-grade presentations
  E. As a complementary tool for quick in-platform BI work
  E. As a complementary tool for quick in-platform BI work

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  Explanation/Reference:

• Question 22:

  Which of the following is an advantage of using a Delta Lake-based data lakehouse over common data lake solutions?

  A. ACID transactions
  B. Flexible schemas
  C. Data deletion
  D. Scalable storage
  E. Open-source formats
  A. ACID transactions

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  Explanation/Reference:

  Reference: https://docs.databricks.com/en/delta/index.html

• Question 23:

  Which of the following statements describes descriptive statistics?

  A. A branch of statistics that uses summary statistics to quantitatively describe and summarize data.
  B. A branch of statistics that uses a variety of data analysis techniques to infer properties of an underlying distribution of probability.
  C. A branch of statistics that uses quantitative variables that must take on a finite or countably infinite set of values.
  D. A branch of statistics that uses summary statistics to categorically describe and summarize data.
  E. A branch of statistics that uses quantitative variables that must take on an uncountable set of values.
  A. A branch of statistics that uses summary statistics to quantitatively describe and summarize data.

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  Explanation/Reference:

• Question 24:

  A data analyst has been asked to produce a visualization that shows the flow of users through a website. Which of the following is used for visualizing this type of flow?

  A. Heatmap
  B. Choropleth
  C. Word Cloud
  D. Pivot Table
  E. Sankey
  E. Sankey

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  Explanation/Reference:

• Question 25:

  A data engineer is working with a nested array column products in table transactions. They want to expand the table so each unique item in products for each row has its own row where the transaction_id column is duplicated as necessary.

  They are using the following incomplete command:

  

  Which of the following lines of code can they use to fill in the blank in the above code block so that it successfully completes the task?

  A. array distinct(products)
  B. explode(products)
  C. reduce(products)
  D. array(products)
  E. flatten(products)
  B. explode(products)

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  Explanation/Reference:

• Question 26:

  A business analyst has been asked to create a data entity/object called sales_by_employee. It should always stay up-to-date when new data are added to the sales table. The new entity should have the columns sales_person, which will be the name of the employee from the employees table, and sales, which will be all sales for that particular sales person. Both the sales table and the employees table have an employee_id column that is used to identify the sales person.

  Which of the following code blocks will accomplish this task?

  

  A. Option A
  B. Option B
  C. Option C
  D. Option D
  E. Option E
  D. Option D

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  Explanation/Reference:

• Question 27:

  Which of the following statements about a refresh schedule is incorrect?

  A. A query can be refreshed anywhere from 1 minute to 2 weeks.
  B. Refresh schedules can be configured in the Query Editor.
  C. A query being refreshed on a schedule does not use a SQL Warehouse (formerly known as SQL Endpoint).
  D. A refresh schedule is not the same as an alert.
  E. You must have workspace administrator privileges to configure a refresh schedule.
  C. A query being refreshed on a schedule does not use a SQL Warehouse (formerly known as SQL Endpoint).

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  Explanation/Reference:

• Question 28:

  A data analyst has created a Query in Databricks SQL, and now they want to create two data visualizations from that Query and add both of those data visualizations to the same Databricks SQL Dashboard. Which of the following steps will they need to take when creating and adding both data visualizations to the Databricks SQL Dashboard?

  A. They will need to alter the Query to return two separate sets of results.
  B. They will need to add two separate visualizations to the dashboard based on the same Query.
  C. They will need to create two separate dashboards.
  D. They will need to decide on a single data visualization to add to the dashboard.
  E. They will need to copy the Query and create one data visualization per query.
  B. They will need to add two separate visualizations to the dashboard based on the same Query.

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  Explanation/Reference:

• Question 29:

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

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  Explanation/Reference:

• Question 30:

  Consider the following two statements:

  

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

  A. 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.
  B. 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.
  C. There is no difference between the result sets for both statements.
  D. Both statements will fail because Databricks SQL does not support those join types.
  E. 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. 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.

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  Explanation/Reference: