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Databricks Databricks-Certified-Data-Analyst-Associate Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Visualization and Dashboards	- Creating dashboards in Databricks SQL 1. Dashboard configuration and sharing 2. Visualizing query results
Topic 2: Databricks SQL and SQL Analytics	- Querying data using SQL in Databricks 1. SELECT statements and filtering data 2. Joins and aggregations - Data transformation and analysis 1. Common table expressions (CTEs) 2. Window functions
Topic 3: Data Management in Lakehouse	- Delta Lake fundamentals 1. ACID transactions and versioning 2. Table optimization concepts - Data ingestion and preparation 1. Batch and streaming ingestion concepts
Topic 4: Data Governance and Security	- Access control and permissions 1. Unity Catalog basics 2. Row-level and column-level security concepts

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Databricks Certified Data Analyst Associate Exam Sample Questions (Q70-Q75):

NEW QUESTION # 70
A data analyst has been asked to provide a list of options on how to share a dashboard with a client. It is a security requirement that the client does not gain access to any other information, resources, or artifacts in the database.
Which of the following approaches cannot be used to share the dashboard and meet the security requirement?

A. Take a screenshot of the dashboard and share it with the client.
B. Generate a Personal Access Token that is good for 1 day and share it with the client.
C. Download a PNG file of the visualizations in the dashboard and share them with the client.
D. Set a refresh schedule for the dashboard and enter the client ' s email address in the " Subscribers " box.
E. Download the Dashboard as a PDF and share it with the client.

Answer: B

Explanation:
The approach that cannot be used to share the dashboard and meet the security requirement is D. Generating a Personal Access Token that is good for 1 day and sharing it with the client. This approach would give the client access to the Databricks workspace using the token owner's identity and permissions, which could expose other information, resources, or artifacts in the database1. The other approaches can be used to share the dashboard and meet the security requirement because:
* A. Downloading the Dashboard as a PDF and sharing it with the client would only provide a static snapshot of the dashboard without any interactive features or access to the underlying data2.
* B. Setting a refresh schedule for the dashboard and entering the client's email address in the
"Subscribers" box would send the client an email with the latest dashboard results as an attachment or a link to a secure web page3. The client would not be able to access the Databricks workspace or the dashboard itself.
* C. Taking a screenshot of the dashboard and sharing it with the client would also only provide a static snapshot of the dashboard without any interactive features or access to the underlying data4.
* E. Downloading a PNG file of the visualizations in the dashboard and sharing them with the client would also only provide a static snapshot of the visualizations without any interactive features or access to the underlying data5. References:
* 1: Personal access tokens
* 2: Download as PDF
* 3: Automatically refresh a dashboard
* 4: Take a screenshot
* 5: Download a PNG file

NEW QUESTION # 71
Which of the following approaches can be used to connect Databricks to Fivetran for data ingestion?

A. Use Workflows to establish a cluster for Fivetran to interact with
B. Use Delta Live Tables to establish a cluster for Fivetran to interact with
C. Use Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
D. Use Partner Connect's automated workflow to establish a cluster for Fivetran to interact with
E. Use Partner Connect's automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with

Answer: D

Explanation:
Partner Connect is a feature that allows you to easily connect your Databricks workspace to Fivetran and other ingestion partners using an automated workflow. You can select a SQL warehouse or a cluster as the destination for your data replication, and the connection details are sent to Fivetran. You can then choose from over 200 data sources that Fivetran supports and start ingesting data into Delta Lake. Reference: Connect to Fivetran using Partner Connect, Use Databricks with Fivetran

NEW QUESTION # 72
What is used as a compute resource for Databricks SQL?

A. Standard clusters
B. Downstream BI tools integrated with Databricks SQL
C. SQL warehouses
D. Single-node clusters

Answer: C

NEW QUESTION # 73
A data analyst is processing a complex aggregation on a table with zero null values and the query returns the following result:

Which query did the analyst execute in order to get this result?

Answer: C

Explanation:
Option D is correct because the table has zero real null values, but the result contains null values representing subtotal and grand-total rows. That behavior is produced by WITH CUBE, which creates aggregations for combinations of grouping columns, including (group_1, group_2), (group_1), (group_2), and the grand total ().
The Databricks SQL documentation states that GROUP BY supports advanced aggregations through CUBE, and that CUBE is shorthand for grouping sets. Option A only returns detailed groups. Options B and C use invalid syntax in Databricks SQL. Reference: Databricks GROUP BY clause documentation.

NEW QUESTION # 74
A data analyst wants the following output:
customer_name
number_of_orders
John Doe
388
Zhang San
234
Which statement will produce this output?

A. SELECT customer_name, count(order_id) AS number_of_ordersFROM customersJOIN ordersON customers.customer_id = orders.customer_idGROUP BY customer_name;
B. SELECT customerjiame, (order_id) number_of_ordersFROM customersJOIN ordersON customers.
customer_id = orders.customer_id;
C. SELECT customerjiame, count(order_id)FROM customersJOIN ordersON customers.customer_id = orders.customer_id GROUP BY customerjiame;
D. SELECT customer_name, count(order_id) number_of_ordersFROM customersJOIN ordersON customers.customer_id = orders.customer_id USE customer_name;

Answer: A

Explanation:
To get the number of orders per customer, you need to join the customers and orders tables on the customer_id, count the order_id, and group the results by customer_name. The correct SQL syntax, as outlined in Databricks SQL documentation, is to use GROUP BY on the selected customer field and use COUNT for aggregation. Only option A does this correctly, while the other options contain syntax errors or incorrect field names.

NEW QUESTION # 75
......

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