Updated Databricks Databricks-Certified-Data-Engineer-Associate Test Cram | Databricks-Certified-Data-Engineer-Associate Free Exam

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Databricks Certified Data Engineer Associate certification is an essential certification for individuals who want to pursue a career in data engineering. Databricks Certified Data Engineer Associate Exam certification exam covers a range of topics and is designed to ensure that candidates have the necessary skills and knowledge to build and maintain large-scale data pipelines. By earning this certification, candidates can demonstrate their expertise in data engineering and increase their chances of getting hired by top companies in the data and AI industry.

Earning the Databricks-Certified-Data-Engineer-Associate Certification can help individuals advance their careers in the field of data engineering. Databricks Certified Data Engineer Associate Exam certification is recognized globally and can demonstrate to employers that the individual has the skills and knowledge required to work with Databricks effectively. It can also lead to better job opportunities and higher salaries.

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q14-Q19):

NEW QUESTION # 14
A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table:

Which of the following changes needs to be made so this code block will work when the transactions table is a stream source?

A. Replace format("delta") with format("stream")
B. Replace schema(schema) with option ("maxFilesPerTrigger", 1)
C. Replace predict with a stream-friendly prediction function
D. Replace spark.read with spark.readStream
E. Replace "transactions" with the path to the location of the Delta table

Answer: D

Explanation:
To read from a stream source, the data engineer needs to use the spark.readStream method instead of the spark.read method. The spark.readStream method returns a DataStreamReader object that can be used to specify the details of the input source, such as the format, the schema, the path, and the options. The spark.read method is only suitable for batch processing, not streaming processing. The other changes are not necessary or correct for reading from a stream source. Reference: Structured Streaming Programming Guide, Read a stream, Databricks Data Sources

NEW QUESTION # 15
A data engineer needs access to a table new_table, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is.
Which of the following approaches can be used to identify the owner of new_table?

A. Review the Owner field in the table's page in Data Explorer
B. Review the Permissions tab in the table's page in Data Explorer
C. All of these options can be used to identify the owner of the table
D. There is no way to identify the owner of the table
E. Review the Owner field in the table's page in the cloud storage solution

Answer: A

NEW QUESTION # 16
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: B

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

NEW QUESTION # 17
A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team's queries uses the same SQL endpoint.
Which of the following approaches can the data engineering team use to improve the latency of the team's queries?

A. They can turn on the Auto Stop feature for the SQL endpoint.
B. They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to
"Reliability Optimized."
C. They can turn on the Serverless feature for the SQL endpoint.
D. They can increase the cluster size of the SQL endpoint.
E. They can increase the maximum bound of the SQL endpoint's scaling range.

Answer: E

Explanation:
https://community.databricks.com/t5/data-engineering/sequential-vs-concurrency-optimization-questions-from-q

NEW QUESTION # 18
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: A

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

NEW QUESTION # 19
......

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UPDATED DATABRICKS DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE TEST CRAM | DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE FREE EXAM

Updated Databricks Databricks-Certified-Data-Engineer-Associate Test Cram | Databricks-Certified-Data-Engineer-Associate Free Exam