The purpose of this Sample Question Set is to provide you with information about the Databricks Certified Data Engineer Associate exam. These sample questions will make you very familiar with both the type and the difficulty level of the questions on the Data Engineer Associate certification test. To get familiar with real exam environment, we suggest you try our Sample Databricks Lakehouse Data Engineer Associate Certification Practice Exam. This sample practice exam gives you the feeling of reality and is a clue to the questions asked in the actual Databricks Certified Data Engineer Associate certification exam.
These sample questions are simple and basic questions that represent likeness to the real Databricks Certified Data Engineer Associate exam questions. To assess your readiness and performance with real-time scenario based questions, we suggest you prepare with our Premium Databricks Data Engineer Associate Certification Practice Exam. When you solve real time scenario based questions practically, you come across many difficulties that give you an opportunity to improve.
Databricks Data Engineer Associate Sample Questions:
01. A data architect is designing a data model that works for both video-based machine learning workloads and highly audited batch ETL/ELT workloads.
Which of the following describes how using a data lakehouse can help the data architect meet the needs of both workloads?
a) A data lakehouse requires very little data modeling.
b) A data lakehouse combines compute and storage for simple governance.
c) A data lakehouse provides autoscaling for compute clusters.
d) A data lakehouse stores unstructured data and is ACID-compliant.
e) A data lakehouse fully exists in the cloud.
02. Which of the following describes a benefit of a data lakehouse that is unavailable in a traditional data warehouse?
a) A data lakehouse provides a relational system of data management.
b) A data lakehouse captures snapshots of data for version control purposes.
c) A data lakehouse couples storage and compute for complete control.
d) A data lakehouse utilizes proprietary storage formats for data.
e) A data lakehouse enables both batch and streaming analytics.
03. A data engineer has created a Delta table as part of a data pipeline. Downstream data analysts now need SELECT permission on the Delta table.
Assuming the data engineer is the Delta table owner, which part of the Databricks Lakehouse Platform can the data engineer use to grant the data analysts the appropriate access?
a) Repos
b) Jobs
c) Data Explorer
d) Databricks Filesystem
e) Dashboards
04. A data engineer has three notebooks in an ELT pipeline. The notebooks need to be executed in a specific order for the pipeline to complete successfully. The data engineer would like to use Delta Live Tables to manage this process.
Which of the following steps must the data engineer take as part of implementing this pipeline using Delta Live Tables?
a) They need to create a Delta Live Tables pipeline from the Data page.
b) They need to create a Delta Live Tables pipeline from the Jobs page.
c) They need to create a Delta Live tables pipeline from the Compute page.
d) They need to refactor their notebook to use Python and the dlt library.
e) They need to refactor their notebook to use SQL and CREATE LIVE TABLE keyword.
05. Which of the following data workloads will utilize a Bronze table as its destination?
a) A job that develops a feature set for a machine learning application
b) A job that queries aggregated data to publish key insights into a dashboard
c) A job that aggregates cleaned data to create standard summary statistics
d) A job that ingests raw data from a streaming source into the Lakehouse
06. A new data engineer has started at a company. The data engineer has recently been added to the company’s Databricks workspace as new.engineer@company.com. The data engineer needs to be able to query the table sales in the database retail. The new data engineer already has been granted USAGE on the database retail.
Which of the following commands can be used to grant the appropriate permissions to the new data engineer?
a) GRANT SELECT ON TABLE sales TO new.engineer@company.com;
b) GRANT CREATE ON TABLE sales TO new.engineer@company.com;
c) GRANT USAGE ON TABLE sales TO new.engineer@company.com;
d) GRANT USAGE ON TABLE new.engineer@company.com TO sales;
e) GRANT SELECT ON TABLE new.engineer@company.com TO sales;
07. A data engineer has set up a notebook to automatically process using a Job. The data engineer’s manager wants to version control the schedule due to its complexity.
Which of the following approaches can the data engineer use to obtain a version-controllable configuration of the Job’s schedule?
a) They can link the Job to notebooks that are a part of a Databricks Repo.
b) They can download the JSON description of the Job from the Job’s page.
c) They can submit the Job once on a Job cluster.
d) They can submit the Job once on an all-purpose cluster.
e) They can download the XML description of the Job from the Job’s page.
08. A new data engineer new.engineer@company.com has been assigned to an ELT project. The new data engineer will need full privileges on the table sales to fully manage the project.
Which of the following commands can be used to grant full permissions on the table to the new data engineer?
a) GRANT ALL PRIVILEGES ON TABLE sales TO new.engineer@company.com;
b) GRANT USAGE ON TABLE sales TO new.engineer@company.com;
c) GRANT ALL PRIVILEGES ON TABLE new.engineer@company.com TO sales;
d) GRANT SELECT ON TABLE sales TO new.engineer@company.com;
e) GRANT SELECT CREATE MODIFY ON TABLE sales TO new.engineer@company.com;
09. Which of the following describes a scenario in which a data engineer will want to use a Job cluster instead of an all-purpose cluster?
a) An ad-hoc analytics report needs to be developed while minimizing compute costs.
b) A data team needs to collaborate on the development of a machine learning model.
c) An automated workflow needs to be run every 30 minutes.
d) A Databricks SQL query needs to be scheduled for upward reporting.
e) A data engineer needs to manually investigate a production error.
10. Two junior data engineers are authoring separate parts of a single data pipeline notebook. They are working on separate Git branches so they can pair program on the same notebook simultaneously. A senior data engineer experienced in Databricks suggests there is a better alternative for this type of collaboration.
Which of the following supports the senior data engineer’s claim?
a) Databricks Notebooks support automatic change-tracking and versioning
b) Databricks Notebooks support real-time coauthoring on a single notebook
c) Databricks Notebooks support commenting and notification comments
d) Databricks Notebooks support the use of multiple languages in the same notebook
e) Databricks Notebooks support the creation of interactive data visualizations
Answers:
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Question: 01 Answer: d |
Question: 02 Answer: e |
Question: 03 Answer: c |
Question: 04 Answer: b |
Question: 05 Answer: d |
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Question: 06 Answer: a |
Question: 07 Answer: b |
Question: 08 Answer: a |
Question: 09 Answer: c |
Question: 10 Answer: b |
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