Databricks Certified Data Analyst Associate Exam Questions Instant Access

Question 1

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?

AAs an exact substitute with the same level of functionality

BAs a substitute with less functionality

CAs a complete replacement with additional functionality

DAs a complementary tool for professional-grade presentations

EAs a complementary tool for quick in-platform Bl work
Databricks SQL is not meant to replace or substitute other BI tools, but rather to complement them by providing a fast and easy way to query, explore, and visualize data on the lakehouse using the built-in SQL editor, visualizations, and dashboards. Databricks SQL also integrates seamlessly with popular BI tools like Tableau, Power BI, and Looker, allowing analysts to use their preferred tools to access data through Databricks clusters and SQL warehouses. Databricks SQL offers low-code and no-code experiences, as well as optimized connectors and serverless compute, to enhance the productivity and performance of BI workloads on the lakehouse.Reference:Databricks SQL,Connecting Applications and BI Tools to Databricks SQL,Databricks integrations overview,Databricks SQL: Delivering a Production SQL Development Experience on the Lakehouse

Answer : E

Question 2

A data analyst is attempting to drop a table my_table. The analyst wants to delete all table metadata and data.

They run the following command:

DROP TABLE IF EXISTS my_table;

While the object no longer appears when they run SHOW TABLES, the data files still exist.

Which of the following describes why the data files still exist and the metadata files were deleted?

AThe table's data was larger than 10 GB

BThe table did not have a location

CThe table was external

DThe table's data was smaller than 10 GB

EThe table was managed
An external table is a table that is defined in the metastore, but its data is stored outside of the Databricks environment, such as in S3, ADLS, or GCS. When an external table is dropped, only the metadata is deleted from the metastore, but the data files are not affected. This is different from a managed table, which is a table whose data is stored in the Databricks environment, and whose data files are deleted when the table is dropped. To delete the data files of an external table, the analyst needs to specify the PURGE option in the DROP TABLE command, or manually delete the files from the storage system.Reference:DROP TABLE,Drop Delta table features,Best practices for dropping a managed Delta Lake table

Answer : C

Question 3

A data analyst has recently joined a new team that uses Databricks SQL, but the analyst has never used Databricks before. The analyst wants to know where in Databricks SQL they can write and execute SQL queries.

On which of the following pages can the analyst write and execute SQL queries?

AData page

BDashboards page

CQueries page

DAlerts page

ESQL Editor page
The SQL Editor page is where the analyst can write and execute SQL queries in Databricks SQL. The SQL Editor page has a query pane where the analyst can type or paste SQL statements, and a results pane where the analyst can view the query results in a table or a chart. The analyst can also browse data objects, edit multiple queries, execute a single query or multiple queries, terminate a query, save a query, download a query result, and more from the SQL Editor page.Reference:Create a query in SQL editor

Answer : E

Question 4

What describes the variance of a set of values?

AVariance is a measure of how far a single observed value is from a set ot va IN

BVariance is a measure of how far an observed value is from the variable's maximum or minimum value.

CVariance is a measure of central tendency of a set of values.

DVariance is a measure of how far a set of values is spread out from the sets central value.
Variance is a statistical measure that quantifies the dispersion or spread of a set of values around their mean (central value). It is calculated by taking the average of the squared differences between each value and the mean of the dataset. A higher variance indicates that the data points are more spread out from the mean, while a lower variance suggests that they are closer to the mean. This measure is fundamental in statistics to understand the degree of variability within a dataset.WikipediaWikipedia+1Investopedia+1

Answer : D

Question 5

A stakeholder has provided a data analyst with a lookup dataset in the form of a 50-row CSV file. The data analyst needs to upload this dataset for use as a table in Databricks SQL.

Which approach should the data analyst use to quickly upload the file into a table for use in Databricks SOL?

ACreate a table by uploading the file using the Create page within Databricks SQL

BCreate a table via a connection between Databricks and the desktop facilitated by Partner Connect.

CCreate a table by uploading the file to cloud storage and then importing the data to Databricks.

DCreate a table by manually copying and pasting the data values into cloud storage and then importing the data to Databricks.
Databricks provides a user-friendly interface that allows data analysts to quickly upload small datasets, such as a 50-row CSV file, and create tables within Databricks SQL. The steps are as follows:
Access the Data Upload Interface:
In the Databricks workspace, navigate to the sidebar and click on New > Add or upload data.
Select Create or modify a table.
Upload the CSV File:
Click on the browse button or drag and drop the CSV file directly onto the designated area.
The interface supports uploading up to 10 files simultaneously, with a total size limit of 2 GB.
Configure Table Settings:
After uploading, a preview of the data is displayed.
Specify the table name, select the appropriate schema, and configure any additional settings as needed.
Create the Table:
Once all configurations are set, click on the Create Table button to finalize the process.
This method is efficient for quickly importing small datasets without the need for additional tools or complex configurations. Options B, C, and D involve more complex or manual processes that are unnecessary for this task.

Answer : A

Question 6

A data analyst wants the following output:

customer_name number_of_orders

John Doe 388

Zhang San 234

Which statement will produce this output?

ASELECT customer_name, count(order_id) AS number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id
GROUP BY customer_name;

BSELECT customer_name, count(order_id) number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id USE customer_name;

CSELECT customerjiame, (order_id) number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id;

DSELECT customerjiame, count(order_id)
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id GROUP BY customerjiame;

Answer : A

Question 7

Which of the following layers of the medallion architecture is most commonly used by data analysts?

ANone of these layers are used by data analysts

BGold

CAll of these layers are used equally by data analysts

DSilver

EBronze
The gold layer of the medallion architecture contains data that is highly refined and aggregated, and powers analytics, machine learning, and production applications. Data analysts typically use the gold layer to access data that has been transformed into knowledge, rather than just information. The gold layer represents the final stage of data quality and optimization in the lakehouse.Reference:What is the medallion lakehouse architecture?

Answer : B