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Databricks Certified Data Analyst Associate Questions 57–64 (page: 9)

Updated On: 12-May-2026

Which statement about subqueries is correct?

  1. Subqueries are not available in Databricks SQL.
  2. Subqueries can be used like other user-defined functions to transform data into different data types.
  3. Subqueries can retrieve data without requiring the creation of a table or view.
  4. Subqueries can be used like other built-in functions to transform data into different data types.

Answer(s): C

Explanation:

Subqueries allow querying data within another SQL query without needing to create a separate table or view.
They are commonly used in SELECT, WHERE, and FROM clauses to filter or compute intermediate results dynamically.



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

  1. Review the Owner field in the table page using Catalog Explorer
  2. Review the Owner field in the database page using Data Explorer
  3. Review the Owner field in the schema page using Data Explorer
  4. Review the Owner field in the table page using the SQL Editor

Answer(s): A

Explanation:

In Databricks SQL, Catalog Explorer provides metadata details about tables, including the Owner field, which indicates who owns the managed table. This is the correct location to determine table ownership.



Which statement about visualizations is true?

  1. All visualizations must use the same data in order to be included in the same Databricks SQL dashboard.
  2. Line charts are the preferred visualization type for categorical data.
  3. Different visualizations can be used to tell different stories about the data.
  4. There is no difference between the bar chart and a histogram in Databricks SQL.

Answer(s): C

Explanation:

Different types of visualizations (e.g., bar charts, line charts, scatter plots) help present data insights in unique ways, depending on the context and analytical goal. Choosing the right visualization enhances understanding and storytelling.



What describes the variance of a set of values?

  1. Variance is a measure of how far a single observed value is from a set of values.
  2. Variance is a measure of how far an observed value is from the variable's maximum or minimum value.
  3. Variance is a measure of central tendency of a set of values.
  4. Variance is a measure of how far a set of values is spread out from the set's central value.

Answer(s): D

Explanation:

Variance quantifies the spread or dispersion of a dataset by measuring how much each value deviates from the mean. A higher variance indicates more spread, while a lower variance suggests that the values are closer to the mean.



Which SQL standards does Databricks SQL use as its default SQL dialect?

  1. Databricks SQL
  2. Spark SQL
  3. ANSI
  4. Delta SQL

Answer(s): C

Explanation:

Databricks SQL follows the ANSI SQL standard as its default SQL dialect. ANSI SQL ensures compatibility with standard SQL syntax and functions, making it easier for users familiar with traditional relational databases to work within Databricks SQL.



A data analyst is working in an organization that utilizes a multi-hop, medallion architecture. They have been tasked with creating a new Gold table from an existing Silver table.

Which query is performing a hop from a Silver table to a Gold table?





Answer(s): C

Explanation:

In the medallion architecture, data moves through different stages:
Bronze (Raw Data) - Ingested from sources.
Silver (Cleaned & Processed Data) - Filtered, deduplicated, and structured.
Gold (Aggregated & Business-ready Data) - Used for reporting and analytics.
The correct query should create store_sales by aggregating sales data using SUM(sales), which is a transformation typically done in the Gold layer. It should process data from cleaned_transactions (a Silver table), making it a Silver Gold transformation.



What is used as a compute resource for Databricks SQL?

  1. Standard clusters
  2. Single-node clusters
  3. SQL warehouses
  4. Downstream BI tools integrated with Databricks SQL

Answer(s): C

Explanation:

In Databricks SQL, SQL warehouses (formerly known as endpoints) are the compute resources specifically optimized for running SQL queries, dashboards, and BI workloads. They provide scalability, concurrency, and performance tuning for analytics.



A data analyst has opened up the SQL Editor page and written a new SQL statement. The data analyst now wants to save that statement to easily refer back to it later to add it to a dashboard. The results of the SQL statement must be able to be displayed as a counter, table, or a data visualization.

Which approach should the data analyst use to accomplish this task?

  1. Save the SQL statement as a Dashboard
  2. Save the SQL statement within a Notebook
  3. Save the SQL statement as a Query
  4. Save the SQL statement in the Query History page

Answer(s): C

Explanation:

In Databricks SQL, saving the statement as a Query allows the analyst to easily retrieve, modify, and add it to a dashboard while also enabling different result visualizations such as counters, tables, and charts. Queries can be reused and shared within Databricks SQL.



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