Databricks Certified Data Analyst Associate Exam Questions Instant Access

Question 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?

AReduce the SQL endpoint cluster size

BIncrease the SQL endpoint cluster size

CTurn off the Auto stop feature

DIncrease the minimum scaling value

EUse a Serverless SQL endpoint
A Serverless SQL endpoint is a type of SQL endpoint that does not require a dedicated cluster to run queries. Instead, it uses a shared pool of resources that can scale up and down automatically based on the demand. This means that a Serverless SQL endpoint can start up much faster than a SQL endpoint that uses a cluster, and it can also save costs by only paying for the resources that are used. A Serverless SQL endpoint is suitable for ad-hoc queries and exploratory analysis, but it may not offer the same level of performance and isolation as a SQL endpoint that uses a cluster. Therefore, a data analyst should consider the trade-offs between speed, cost, and quality when choosing between a Serverless SQL endpoint and a SQL endpoint that uses a cluster.Reference:Databricks SQL endpoints,Serverless SQL endpoints,SQL endpoint clusters

Answer : E

Question 2

A data scientist has asked a data analyst to create histograms for every continuous variable in a data set. The data analyst needs to identify which columns are continuous in the data set.

What describes a continuous variable?

AA quantitative variable that never stops changing

BA quantitative variable Chat can take on a finite or countably infinite set of values

CA quantitative variable that can take on an uncountable set of values

DA categorical variable in which the number of categories continues to increase over time
A continuous variable is a type of quantitative variable that can assume an infinite number of values within a given range. This means that between any two possible values, there can be an infinite number of other values. For example, variables such as height, weight, and temperature are continuous because they can be measured to any level of precision, and there are no gaps between possible values. This is in contrast to discrete variables, which can only take on specific, distinct values (e.g., the number of children in a family). Understanding the nature of continuous variables is crucial for data analysts, especially when selecting appropriate statistical methods and visualizations, such as histograms, to accurately represent and analyze the data.

Answer : C

Question 3

Which of the following approaches can be used to ingest data directly from cloud-based object storage?

ACreate an external table while specifying the DBFS storage path to FROM

BCreate an external table while specifying the DBFS storage path to PATH

CIt is not possible to directly ingest data from cloud-based object storage

DCreate an external table while specifying the object storage path to FROM

ECreate an external table while specifying the object storage path to LOCATION
External tables are tables that are defined in the Databricks metastore using the information stored in a cloud object storage location. External tables do not manage the data, but provide a schema and a table name to query the data. To create an external table, you can use the CREATE EXTERNAL TABLE statement and specify the object storage path to the LOCATION clause. For example, to create an external table named ext_table on a Parquet file stored in S3, you can use the following statement:
SQL
CREATE EXTERNAL TABLE ext_table (
col1 INT,
col2 STRING
)
STORED AS PARQUET
LOCATION 's3://bucket/path/file.parquet'
AI-generated code. Review and use carefully.More info on FAQ.

Answer : E

Question 4

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

AReview the Owner field in the table page using Catalog Explorer

BReview the Owner field in the database page using Data Explorer

CReview the Owner field in the schema page using Data Explorer

DReview the Owner field in the table page using the SQL Editor
In Databricks, to determine the owner of a managed table, you can utilize the Catalog Explorer feature. The steps are as follows:
Access Catalog Explorer:
In your Databricks workspace, click on the Catalog icon in the sidebar to open Catalog Explorer.
Navigate to the Table:
Within Catalog Explorer, browse through the catalog and schema to locate the specific managed table whose ownership you wish to verify.
View Table Details:
Click on the table name to open its details page.
Identify the Owner:
On the table's details page, review the Owner field, which displays the principal (user, service principal, or group) that owns the table.
This method provides a straightforward way to ascertain the ownership of managed tables within the Databricks environment. Understanding table ownership is essential for managing permissions and ensuring proper access control.

Answer : A

Question 5

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

Question 6

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 7

A data analyst needs to share a Databricks SQL dashboard with stakeholders that are not permitted to have accounts in the Databricks deployment. The stakeholders need to be notified every time the dashboard is refreshed.

Which approach can the data analyst use to accomplish this task with minimal effort/

ABy granting the stakeholders' email addresses permissions to the dashboard

BBy adding the stakeholders' email addresses to the refresh schedule subscribers list

CBy granting the stakeholders' email addresses to the SQL Warehouse (formerly known as endpoint) subscribers list

DBy downloading the dashboard as a PDF and emailing it to the stakeholders each time it is refreshed
To share a Databricks SQL dashboard with stakeholders who do not have accounts in the Databricks deployment and ensure they are notified upon each refresh, the data analyst can add the stakeholders' email addresses to the dashboard's refresh schedule subscribers list. This approach allows the stakeholders to receive email notifications containing the latest dashboard updates without requiring them to have direct access to the Databricks workspace. This method is efficient and minimizes effort, as it automates the notification process and ensures stakeholders remain informed of the most recent data insights.

Answer : B