Databricks-Certified-Data-Engineer-Associate dumps: Databricks Certified Data Engineer Associate Exam & Databricks-Certified-Data-Engineer-Associate exam VCE

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

Section	Objectives
Topic 1: Databricks Lakehouse Platform Fundamentals	- Clusters, notebooks, and basic Databricks environment usage - Workspace, architecture, and core platform concepts
Topic 2: Data Governance and Quality	- Data access control and governance - Unity Catalog basics - Data quality concepts and management
Topic 3: Data Ingestion and ELT Development	- Data ingestion using Spark SQL and PySpark - Handling structured and semi-structured data - ETL patterns and transformations
Topic 4: Productionizing Data Pipelines	- Pipeline deployment and operationalization - Databricks Workflows / Jobs orchestration - Scheduling and monitoring jobs
Topic 5: Data Processing and Transformations	- Apache Spark SQL operations (joins, aggregations, filtering) - PySpark DataFrame transformations - User-defined functions (UDFs) - Delta Lake fundamentals (tables, transactions, optimization)

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q135-Q140):

NEW QUESTION # 135
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Answer: C

Explanation:
https://www.databricks.com/blog/2021/10/20/introducing-sql-user-defined-functions.html

NEW QUESTION # 136
A data engineer is designing a bronze-to-silver pipeline on the Databricks Data Intelligence Platform. The source system sends daily CSV files, and over time, new optional columns are added.
The data engineer wants a storage format and table feature that together ensure the following:
- The table prevents writes that do not conform to the defined schema.
- The table can evolve its schema to include new optional columns
without having to manually recreate the table.
- Previous versions of the table can be queried later for debugging and auditing.
Which solution fulfills the requirements?

A. Use a Delta table with schema enforcement and recreate the table whenever new columns are added.
B. Use a Parquet table with Spark's default schema inference and rely on re-running the job when the schema changes.
C. Use an external table with Auto Loader schema inference for CSV files.
D. Use a Delta table with its native capabilities.

Answer: D

Explanation:
Delta Lake provides schema enforcement, supports schema evolution for newly added columns, and retains table history for time travel and auditing.

NEW QUESTION # 137
A new data engineering team has been assigned to work on a project. The team will need access to database customers in order to see what tables already exist. The team has its own group team.
Which of the following commands can be used to grant the necessary permission on the entire database to the new team?

A. GRANT USAGE ON CATALOG team TO customers;
B. GRANT CREATE ON DATABASE team TO customers;
C. GRANT VIEW ON CATALOG customers TO team;
D. GRANT CREATE ON DATABASE customers TO team;
E. GRANT USAGE ON DATABASE customers TO team;

Answer: E

NEW QUESTION # 138
A data engineer that is new to using Python needs to create a Python function to add two integers together and return the sum?
Which of the following code blocks can the data engineer use to complete this task?

Answer: A

Explanation:
https://www.w3schools.com/python/python_functions.asp
https://www.geeksforgeeks.org/python-functions/

NEW QUESTION # 139
Which Databricks feature can be used to check the data sources and tables used in a workspace?

A. Use the audit logs feature to review user activities, such as who queried or modified a table, instead of visualizing dependencies between data objects.
B. Use the lineage feature to visualize a graph that highlights where the table is used only in reports.
C. Use the lineage feature to visualize a graph that shows all dependencies, including where the table is used in notebooks, other tables, and reports.
D. Use the lineage feature to visualize a graph that highlights where the table is used only in notebooks.

Answer: C

Explanation:
The lineage feature provides a visual graph of end-to-end data dependencies, showing data sources, tables, notebooks, and downstream consumers such as reports, enabling visibility into how data is produced and used across the workspace.

NEW QUESTION # 140
......

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