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

Section	Objectives
Data Ingestion and ELT Development	- Data ingestion using Spark SQL and PySpark - ETL patterns and transformations - Handling structured and semi-structured data
Productionizing Data Pipelines	- Scheduling and monitoring jobs - Databricks Workflows / Jobs orchestration - Pipeline deployment and operationalization
Databricks Lakehouse Platform Fundamentals	- Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage
Data Processing and Transformations	- PySpark DataFrame transformations - User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) - Delta Lake fundamentals (tables, transactions, optimization)
Data Governance and Quality	- Data quality concepts and management - Data access control and governance - Unity Catalog basics

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q294-Q299):

NEW QUESTION # 294
A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start.
Which of the following actions can the data engineer perform to improve the start up time for the clusters used for the Job?

A. They can use endpoints available in Databricks SQL
B. They can use jobs clusters instead of all-purpose clusters
C. They can use clusters that are from a cluster pool
D. They can configure the clusters to autoscale for larger data sizes
E. They can configure the clusters to be single-node

Answer: C

Explanation:
Explanation
Cluster pools are a way to pre-provision clusters that are ready to use. This can reduce the start up time for clusters, as they do not have to be created from scratch. All-purpose clusters are not pre-provisioned, so they will take longer to start up. Jobs clusters are a type of cluster pool, but they are not the best option for this use case. Jobs clusters are designed for long-running jobs, and they can be more expensive than other types of cluster pools. Single-node clusters are the smallest type of cluster, and they will start up the fastest. However, they may not be powerful enough to run the Job's tasks. Autoscaling clusters can scale up or down based on demand. This can help to improve the start up time for clusters, as they will only be created when they are needed. However, autoscaling clusters can also be more expensive than other types of cluster pool
https://docs.databricks.com/en/clusters/pool-best-practices.html

NEW QUESTION # 295
A data engineer manages multiple external tables linked to various data sources. The data engineer wants to manage these external tables efficiently and ensure that only the necessary permissions are granted to users for accessing specific external tables. How should the data engineer manage access to these external tables?

A. Grant permissions on the Databricks workspace level, which will automatically apply to all external tables.
B. Use Unity Catalog to manage access controls and permissions for each external table individually.
C. Create a single user role with full access to all external tables and assign it to all users.
D. Set up Azure Blob Storage permissions at the container level, allowing access to all external tables.

Answer: B

Explanation:
The correct approach is to use Unity Catalog to manage fine-grained access controls and permissions for each external table individually. Unity Catalog centralizes governance and ensures users only have access to the specific external tables they need, instead of granting broad storage or workspace-level permissions.

NEW QUESTION # 296
Which of the following tools is used by Auto Loader process data incrementally?

A. Checkpointing
B. Unity Catalog
C. Databricks SQL
D. Data Explorer
E. Spark Structured Streaming

Answer: E

NEW QUESTION # 297
A data engineer needs to create a table in Databricks using data from a CSV file at location /path/to/csv.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

A. None of these lines of code are needed to successfully complete the task
B. USING DELTA
C. FROM CSV
D. USING CSV
E. FROM "path/to/csv"

Answer: D

NEW QUESTION # 298
Which two conditions are applicable for governance in Databricks Unity Catalog? (Choose two.)

A. Both catalog and schema must have a managed location in Unity Catalog provided metastore is not associated with a location
B. If metastore is not associated with location, it's mandatory to associate catalog with managed locations
C. You can have multiple catalogs within metastore and 1 catalog can be associated with multiple metastore
D. You can have more than 1 metastore within a databricks account console but only 1 per region.
E. If catalog is not associated with location, it's mandatory to associate schema with managed locations

Answer: B,D

Explanation:
You can have more than 1 metastore within a Databricks account console but only 1 per region:
This is correct. In Databricks Unity Catalog, you can create multiple metastores, but you can only have one metastore per region within an account.
If metastore is not associated with location, it's mandatory to associate catalog with managed locations: This is also correct. If a metastore does not have a default storage location, then the catalog must be associated with a managed location to ensure that data is stored properly within Unity Catalog.

NEW QUESTION # 299
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