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

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Databricks Certified Data Analyst Associate Exam Sample Questions (Q35-Q40):

NEW QUESTION # 35
An analyst has been asked to combine the data in two tables: suppliers and new_suppliers. It is possible that some of the supplier_id values match in both tables, meaning those suppliers have already been added to the suppliers table. If that is the case, the data should be unchanged.
Which command will combine the two tables without duplicating the rows with the same supplier_id?

A. Option DINSERT INTO suppliersUSING new_suppliersON suppliers.supplier_id = new_suppliers.
supplier_idWHEN NOT MATCHED THEN INSERT *;
B. Option BCOPY INTO suppliersUSING new_suppliersON suppliers.supplier_id = new_suppliers.
supplier_idWHEN NOT MATCHED THEN INSERT *;
C. Option CUPDATE suppliersUSING new_suppliersON suppliers.supplier_id = new_suppliers.
supplier_idWHEN NOT MATCHED THEN INSERT *;
D. Option AMERGE INTO suppliersUSING new_suppliersON suppliers.supplier_id = new_suppliers.
supplier_idWHEN NOT MATCHED THEN INSERT *;

Answer: D

Explanation:
The correct answer is A because MERGE INTO is the Databricks SQL command used to combine source rows with a target table based on a match condition. The condition checks whether supplier_id already exists.
If a row does not match, WHEN NOT MATCHED THEN INSERT * inserts it. If a row already matches, no WHEN MATCHED action is provided, so the existing row remains unchanged. This prevents duplicate supplier rows.
Official documentation extract used: Databricks shows the pattern MERGE INTO target USING source ON target.key = source.key WHEN NOT MATCHED THEN INSERT *.

NEW QUESTION # 36
In which of the following scenarios should a data engineer select a Task in the Depends On field of a new Databricks Job Task?

A. When another task needs to successfully complete before the new task begins.
B. When another task needs to use as little compute resources as possible.
C. When another task needs to be replaced by the new task.
D. When another task needs to fail before the new task begins.
E. When another task has the same dependency libraries as the new task.

Answer: A

Explanation:
Option E is correct. The Depends On field is used to define task dependencies in a Databricks job, so a downstream task waits for an upstream task according to the dependency rules. The standard use case is when one task must complete successfully before the next task starts. Official Databricks extract: "You can control the execution order of tasks by specifying dependencies between them," and Databricks runs upstream tasks before downstream tasks.

NEW QUESTION # 37
A business analyst has been asked to create a data entity/object called sales_by_employee. It should always stay up-to-date when new data are added to the sales table. The new entity should have the columns sales_person, which will be the name of the employee from the employees table, and sales, which will be all sales for that particular sales person. Both the sales table and the employees table have an employee_id column that is used to identify the sales person.
Which of the following code blocks will accomplish this task?

Answer: A

Explanation:
The SQL code provided in Option D is the correct way to create a view named sales_by_employee that will always stay up-to-date with the sales and employees tables. The code uses the CREATE OR REPLACE VIEW statement to define a new view that joins the sales and employees tables on the employee_id column. It selects the employee_name as sales_person and all sales for each employee, ensuring that the data entity
/object is always up-to-date when new data are added to these tables.
The answer can be verified from Databricks SQL documentation which provides insights on creating views using SQL queries, joining tables, and selecting specific columns to be included in the view. Reference link: Databricks SQL

NEW QUESTION # 38
A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.
Which of the following commands can the analyst use to complete the task without producing an error?

A. DELETE TABLE table_name FROM database_name;
B. DROP DATABASE database_name;
C. DROP TABLE database_name.table_name;
D. DELETE TABLE database_name.table_name;
E. DROP TABLE table_name FROM database_name;

Answer: C

NEW QUESTION # 39
A data analyst is using Databricks Unity Catalog. The datasets are tagged by sensitivity, and confidential data is marked with the tag key confidential. The data analyst needs to quickly find all tables tagged as confidential to review their access permissions in the Databricks workspace search bar.
Which search key text should the data analyst use to find these tables?

A. tag=confidential
B. tag:confidential
C. search tag = ' confidential '
D. confidential:true

Answer: B

Explanation:
The correct answer is C because the tag key is confidential, and Databricks workspace search uses the syntax tag: < tag_key > to search by tag key. Therefore, the correct search text is tag:confidential. Option A uses a Boolean-style syntax that is not the documented Databricks tag search syntax. Option B uses an equals sign, and Option D is not valid workspace search syntax.
Official documentation extract used: Databricks states that to search by tag key alone, use the syntax tag: < tag_key > .

NEW QUESTION # 40
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