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

Section	Weight	Objectives
Topic 1: Delta Lake Fundamentals	20-25%	- Create and manage Delta tables - Explain Delta Lake features and benefits - Understand ACID transactions and time travel - Write to and read from Delta tables
Topic 2: Data Pipeline Architecture	15-20%	- Design data pipelines for batch and streaming - Monitor and optimize pipeline performance - Implement incremental data processing - Understand ELT vs ETL patterns
Topic 3: Apache Spark Data Processing Fundamentals	20-25%	- Use Spark SQL for data processing - Create and use Spark DataFrames - Apply transformations and actions on DataFrames - Work with structured data types (arrays, maps, structs)
Topic 4: Spark SQL and DataFrames	15-20%	- Handle null values and data quality - Write and execute Spark SQL queries - Aggregate and group data - Join and union DataFrames
Topic 5: Lakehouse Platform Concepts	10-15%	- Explain data governance and security concepts - Understand the Lakehouse architecture and its benefits - Describe key Databricks Lakehouse platform components
Topic 6: Python for Data Engineering	10-15%	- Use PySpark for data processing - Implement user-defined functions (UDFs) - Work with Spark APIs in Python

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q42-Q47):

NEW QUESTION # 42
A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the original task.
Which of the following approaches can the data engineer use to set up the new task?

A. They can clone the existing task to a new Job and then edit it to run the new notebook.
B. They can create a new task in the existing Job and then add the original task as a dependency of the new task.
C. They can clone the existing task in the existing Job and update it to run the new notebook.
D. They can create a new task in the existing Job and then add it as a dependency of the original task.
E. They can create a new job from scratch and add both tasks to run concurrently.

Answer: D

Explanation:
Explanation
To set up the new task to run a new notebook prior to the original task in a single-task Job, the data engineer can use the following approach: In the existing Job, create a new task that corresponds to the new notebook that needs to be run. Set up the new task with the appropriate configuration, specifying the notebook to be executed and any necessary parameters or dependencies. Once the new task is created, designate it as a dependency of the original task in the Job configuration. This ensures that the new task is executed before the original task.

NEW QUESTION # 43
A data engineer wants to delegate day-to-day permission management for the schema main marketing to the mkt-admins group, without making them workspace admins. They should be able to grant and revoke privileges for other users on objects within that schema.
Which approach aligns with UC's ownership and privilege model?

A. Grant MANAGE permissions on the metastore to mkt-admins, which allows managing privileges for all schemas and tables globally.
B. Make mkt-admins a workspace-level admins group, then SELECT on main.marketing to allow privilege delegation.
C. Grant USE SCHEMA on main.marketing and MODIFY on all tables to mkt-admins, which enables managing grants within the schema.
D. Transfer ownership of the schema main.marketing to mkt-admins; owners can manage privileges on the schema and its contained objects.

Answer: D

Explanation:
In Unity Catalog, object owners have full control over privilege management for that object and its children. Transferring ownership of the schema to the group allows it to grant and revoke privileges within the schema without requiring workspace-level administrative rights.

NEW QUESTION # 44
A Databricks Job with four sequential tasks is executed. The job failed at Task 3. After the root cause is fixed, the data engineer needs to complete the workflow without re-running the successful Tasks 1 and 2. Which action in the Job Run details page allows the engineer to resume execution from the point of failure?

A. Reset job
B. Repair run
C. Clone task
D. Run now

Answer: B

Explanation:
Repair run reruns the failed Task 3 and any dependent downstream tasks while preserving the successful results of Tasks 1 and 2.

NEW QUESTION # 45
A data engineer needs to enforce row-level security on main.secure.events(region STRING, event_id STRING). Members of the account group all_regions must see all rows. All other users must see only rows where region = 'EU'.
Which SQL sequence satisfies the requirement?

A. CREATE FUNCTION main.secure.region_filter(region STRING)
RETURN IF(is_account_group_member('all_regions'), true, region = 'EU'); ALTER TABLE main.secure.events SET ROW FILTER main.secure.region_filter USING COLUMNS (region);
B. CREATE FUNCTION main.secure.region_filter(region STRING)
RETURN IF(is_account_group_member('all_regions'), true, region = 'EU'); ALTER TABLE main.secure.events ALTER COLUMN region SET MASK main.secure.region_filter;
C. CREATE FUNCTION main.secure.region_filter(region STRING)
RETURN IF(is_account_group_member('all_regions'), true, region = 'EU'); ALTER TABLE main.secure.events SET ROW FILTER main.secure.region_filter ON (region);
D. CREATE FUNCTION main.secure.region_filter(region STRING)
RETURN IF(is_account_group_member('all_regions'), true, region = 'EU'); ALTER VIEW main.secure.events SET ROW FILTER main.secure.region_filter ON (region);

Answer: C

Explanation:
A row-filter function must return a Boolean value indicating whether each row is visible to the current user. The function in option A returns true for members of the account-level all_regions group, allowing them to see every row. For other users, it returns the result of region = 'EU', limiting visibility to European records. is_account_group_member checks direct or indirect membership in an account-level group. The ALTER TABLE ... SET ROW FILTER ... ON (region) statement then associates the function with the table and passes the region column to it for every query. A column mask transforms displayed column values rather than removing rows. The object is a table, not a view, and USING COLUMNS is not the correct row-filter attachment syntax. Therefore, option A is correct.

NEW QUESTION # 46
A data engineer is working on a Databricks project that utilizes cloud storage. The data engineer wants to load several json files from containers on a storage account as soon as the file arrives within the storage account.
Which syntax should the data engineer follow to first load the files into a dataframe and check that it is working as expected using Python?

A. df = spark.read.json("inp i./path")
B. df = spark.readStream.format("json").load("input/path")
C. df = spark.readStream.format("cloudFiles") .option("cloudFiles.format", "json") .load("/input/path")
D. df = spark.readStream.format("cloud"),option("json").load("/input/path")

Answer: C

NEW QUESTION # 47
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