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Databricks-Certified-Data-Analyst-Associate Exam Info
Databricks-Certified-Data-Analyst-Associate Exam Questions

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Databricks-Certified-Data-Analyst-Associate Exam Questions

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Question 1

A data analyst wants to create a Databricks SQL dashboard with multiple data visualizations and multiple counters. What must be completed before adding the data visualizations and counters to the dashboard?

AAll data visualizations and counters must be created using Queries.

BA SQL warehouse (formerly known as SQL endpoint) must be turned on and selected.

CA markdown-based tile must be added to the top of the dashboard displaying the dashboard's name.

DThe dashboard owner must also be the owner of the queries, data visualizations, and counters.
In Databricks SQL, when creating a dashboard that includes multiple data visualizations and counters, it is imperative that each visualization and counter is based on a query. The process involves the following steps:
Develop Queries:
For each desired visualization or counter, write a SQL query that retrieves the necessary data.
Create Visualizations and Counters:
After executing each query, utilize the results to create corresponding visualizations or counters. Databricks SQL offers a variety of visualization types to represent data effectively.
Assemble the Dashboard:
Add the created visualizations and counters to your dashboard, arranging them as needed to convey the desired insights.
By ensuring that all components of the dashboard are derived from queries, you maintain consistency, accuracy, and the ability to refresh data as needed. This approach also facilitates easier maintenance and updates to the dashboard elements.

Correct : A

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AAll data visualizations and counters must be created using Queries.

BA SQL warehouse (formerly known as SQL endpoint) must be turned on and selected.

CA markdown-based tile must be added to the top of the dashboard displaying the dashboard's name.

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Question 2

After running DESCRIBE EXTENDED accounts.customers;, the following was returned:

Now, a data analyst runs the following command:

DROP accounts.customers;

Which of the following describes the result of running this command?

ARunning SELECT * FROM delta. `dbfs:/stakeholders/customers` results in an error.

BRunning SELECT * FROM accounts.customers will return all rows in the table.

CAll files with the .customers extension are deleted.

DThe accounts.customers table is removed from the metastore, and the underlying data files are deleted.

EThe accounts.customers table is removed from the metastore, but the underlying data files are untouched.
the accounts.customers table is an EXTERNAL table, which means that it is stored outside the default warehouse directory and is not managed by Databricks. Therefore, when you run the DROP command on this table, it only removes the metadata information from the metastore, but does not delete the actual data files from the file system. This means that you can still access the data using the location path (dbfs:/stakeholders/customers) or create another table pointing to the same location. However, if you try to query the table using its name (accounts.customers), you will get an error because the table no longer exists in the metastore.Reference:DROP TABLE | Databricks on AWS,Best practices for dropping a managed Delta Lake table - Databricks

Correct : E

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ARunning SELECT * FROM delta. `dbfs:/stakeholders/customers` results in an error.

BRunning SELECT * FROM accounts.customers will return all rows in the table.

CAll files with the .customers extension are deleted.

DThe accounts.customers table is removed from the metastore, and the underlying data files are deleted.

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Question 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 10 minutes.

A data analyst has created a dashboard based on this gold level dat

a. The project stakeholders want to see the results in the dashboard updated within 10 minutes or less of new data becoming available within the gold-level tables.

What is the ability to ensure the streamed data is included in the dashboard at the standard requested by the project stakeholders?

AA refresh schedule with an interval of 10 minutes or less

BA refresh schedule with an always-on SQL Warehouse (formerly known as SQL Endpoint

CA refresh schedule with stakeholders included as subscribers

DA refresh schedule with a Structured Streaming cluster
In this scenario, the data engineering team has configured a Structured Streaming pipeline that updates the gold-level tables every 10 minutes. To ensure that the dashboard reflects the most recent data, it is essential to set the dashboard's refresh schedule to an interval of 10 minutes or less. This synchronization ensures that stakeholders view the latest information shortly after it becomes available in the gold-level tables. Options B, C, and D do not directly address the requirement of aligning the dashboard refresh frequency with the data update interval.

Correct : A

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AA refresh schedule with an interval of 10 minutes or less

BA refresh schedule with an always-on SQL Warehouse (formerly known as SQL Endpoint

CA refresh schedule with stakeholders included as subscribers

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Question 4

The stakeholders.customers table has 15 columns and 3,000 rows of dat

a. The following command is run:

After running SELECT * FROM stakeholders.eur_customers, 15 rows are returned. After the command executes completely, the user logs out of Databricks.

After logging back in two days later, what is the status of the stakeholders.eur_customers view?

AThe view remains available and SELECT * FROM stakeholders.eur_customers will execute correctly.

BThe view has been dropped.

CThe view is not available in the metastore, but the underlying data can be accessed with SELECT * FROM delta. `stakeholders.eur_customers`.

DThe view remains available but attempting to SELECT from it results in an empty result set because data in views are automatically deleted after logging out.

EThe view has been converted into a table.
In Databricks, a view is a saved SQL query definition that references existing tables or other views. Once created, a view remains persisted in the metastore (such as Unity Catalog or Hive Metastore) until it is explicitly dropped.
Key points:
Views do not store data themselves but reference data from underlying tables.
Logging out or being inactive does not delete or alter views.
Unless a user or admin explicitly drops the view or the underlying data/table is deleted, the view continues to function as expected.
Therefore, after logging back in---even days later---a user can still run SELECT * FROM stakeholders.eur_customers, and it will return the same data (provided the underlying table hasn't changed).

Correct : A

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AThe view remains available and SELECT * FROM stakeholders.eur_customers will execute correctly.

BThe view has been dropped.

CThe view is not available in the metastore, but the underlying data can be accessed with SELECT * FROM delta. `stakeholders.eur_customers`.

DThe view remains available but attempting to SELECT from it results in an empty result set because data in views are automatically deleted after logging out.

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Question 5

Data professionals with varying responsibilities use the Databricks Lakehouse Platform Which role in the Databricks Lakehouse Platform use Databricks SQL as their primary service?

AData scientist

BData engineer

CPlatform architect

DBusiness analyst
In the Databricks Lakehouse Platform, business analysts primarily utilize Databricks SQL as their main service. Databricks SQL provides an environment tailored for executing SQL queries, creating visualizations, and developing dashboards, which aligns with the typical responsibilities of business analysts who focus on interpreting data to inform business decisions. While data scientists and data engineers also interact with the Databricks platform, their primary tools and services differ; data scientists often engage with machine learning frameworks and notebooks, whereas data engineers focus on data pipelines and ETL processes. Platform architects are involved in designing and overseeing the infrastructure and architecture of the platform. Therefore, among the roles listed, business analysts are the primary users of Databricks SQL.

Correct : D

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AData scientist

BData engineer

CPlatform architect

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Total 65 questions

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Databricks Certified Data Analyst Associate Exam

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