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Databricks Databricks-Certified-Data-Engineer-Associate Exam Overview:

Certification Vendor:	Databricks
Exam Name:	Databricks Certified Data Engineer Associate Exam
Exam Number:	DE-A
Certificate Validity Period:	2 years
Real Exam Qty:	45 scored multiple-choice questions
Available Languages:	English
Exam Price:	USD 200
Exam Format:	Proctored online or test center, Multiple-choice, Scenario-based questions
Exam Duration:	90 minutes
Passing Score:	Approximately ~70% (not officially fixed/publicly guaranteed)
Related Certifications:	Databricks Certified Data Engineer Professional
Recommended Training:	Official Data Engineering with Databricks Course Databricks Data Engineering Learning Path (Databricks Academy)
Exam Registration:	Databricks Certification Portal
Sample Questions:	Databricks Databricks-Certified-Data-Engineer-Associate Sample Questions
Exam Way:	Online proctored exam or test center
Pre Condition:	No formal prerequisites required; recommended ~6 months hands-on experience with Databricks, Spark SQL, and PySpark.
Official Syllabus URL:	https://www.databricks.com/learn/certification/data-engineer-associate

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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Exam is a certification exam that tests the skills and knowledge of individuals in the field of data engineering using Databricks. Databricks is a cloud-based data platform that allows data engineers to build, manage, and deploy data pipelines at scale. Databricks-Certified-Data-Engineer-Associate exam is designed to assess an individual's proficiency in using Databricks to perform tasks such as data transformation, data ingestion, and data analysis.

Databricks Certified Data Engineer Associate exam is designed for data engineers who work with the Databricks platform and have experience in designing and implementing data pipelines. Databricks-Certified-Data-Engineer-Associate Exam covers a wide range of topics, including data ingestion, transformation, storage, and processing. It also covers advanced concepts such as Spark architecture, performance tuning, and optimization.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q220-Q225):

NEW QUESTION # 220
Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

A. Data lake
B. Data warehouse
C. All of these
D. Data lakehouse
E. None of these

Answer: D

NEW QUESTION # 221
A data engineer has developed a Python notebook in a Databricks workspace and configured it to run as a scheduled job to process daily sales data.
How are the storage and execution of this notebook managed within the Databricks architecture?

A. The notebook is stored securely and encrypted in the compute plane, and the code executes in the control plane when the job runs.
B. The notebook is stored securely and encrypted in Unity Catalog, and the code executes in Delta Lake when the job runs.
C. The notebook is stored securely and encrypted in the control plane, and the code executes in the compute plane when the job runs.
D. The notebook is stored unencrypted in the workspace storage bucket, and the code executes on the cluster driver node in the compute plane when the job runs.

Answer: C

NEW QUESTION # 222
A data engineer is implementing a data ingestion pipeline that automatically detects schema changes in incoming JSON files and evolves the target Delta table accordingly. Which feature supports this automatic schema evolution?

A. Broadcast join
B. Schema enforcement
C. Partition pruning
D. Schema evolution

Answer: D

NEW QUESTION # 223
A data engineering team is building a new data-transformation notebook. During development, the engineers need fast testing, quick code changes, and easy debugging. Later, the notebook will run nightly as a scheduled job without human intervention. The team wants to optimize for development speed.
Which compute should the team use during development?

A. Interactive compute
B. An instance pool
C. A SQL warehouse
D. Classic jobs compute

Answer: A

NEW QUESTION # 224
A data engineer needs to find all customers who have never placed an order. The customers table contains customer_id, customer_name, and other customer attributes. The orders table contains order_id, customer_id, and other order attributes. Both tables share customer_id as the join key. The result must include only customer columns, with no order-related columns in the output.
Which expression exactly achieves this requirement?

A. A left anti-join from customers to orders
B. A full outer join followed by filtering where order_id IS NULL
C. An inner join followed by filtering for a NULL order_id
D. A left outer join from orders to customers

Answer: A

NEW QUESTION # 225
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