Free Access Snowflake.DEA-C01.v2026-09-04.q215 Practice Test (Page 6)

Question 21

A data engineer needs to analyze time-sensitive sales data. The company stores the data in an Amazon S3 bucket. The data engineer uses AWS Glue Data Catalog to access the data.
When the data engineer performs the analysis, the data engineer notices that some records are missing or out of date.
What is the likely cause of these issues?

A.AWS Glue Data Catalog is not up to date with the latest S3 partition changes.

B.Incorrect IAM roles are assigned to the AWS Glue jobs.

C.Versioning is not enabled on the S3 bucket.

D.The AWS Glue job schedules overlap with one another.

Question 22

An ecommerce company collects daily customer transaction logs in CSV format and stores the logs in Amazon S3. The company uses Amazon Athena to scan a subset of attributes from the logs on the same day the company receives each log.
Query times are increasing because of increasing transaction volume. The company wants to improve query performance.
Which solution will meet these requirements with the SHORTEST query times?

A.Convert the CSV logs into multiple ORC files for better parallelism in Athena. Partition by date in Amazon S3. Use columnar pushdown filters.

B.Convert the CSV logs to JSON. Partition by date in Amazon S3. Use Athena with dynamic filtering to reduce data scans.

C.Convert the CSV logs to Avro. Partition by date in Amazon S3. Use Athena with projection-based partitioning.

D.Convert the CSV logs to a single Apache Parquet file for each day Partition the data by date in Amazon S3. Use Athena with predicate pushdown filters.

Question 23

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.
The data engineer must identify and remove duplicate information from the legacy application data.
Which solution will meet these requirements with the LEAST operational overhead?

A.Write an AWS Glue extract, transform, and load (ETL) job. Use the FindMatches machine learning (ML) transform to transform the data to perform data deduplication.

B.Write an AWS Glue extract, transform, and load (ETL) job. Import the Python dedupe library. Use the dedupe library to perform data deduplication.

C.Write a custom extract, transform, and load (ETL) job in Python. Use the DataFrame.drop_duplicates() function by importing the Pandas library to perform data deduplication.

D.Write a custom extract, transform, and load (ETL) job in Python. Import the Python dedupe library. Use the dedupe library to perform data deduplication.

Question 24

A data engineer needs to use an Amazon QuickSight dashboard that is based on Amazon Athena queries on data that is stored in an Amazon S3 bucket. When the data engineer connects to the QuickSight dashboard, the data engineer receives an error message that indicates insufficient permissions.
Which factors could cause to the permissions-related errors? (Choose two.)

A.There is no connection between QuickSight and Athena.

B.The Athena tables are not cataloged.

C.QuickSight does not have access to the S3 bucket.

D.QuickSight does not have access to decrypt S3 data.

E.There is no IAM role assigned to QuickSight.

Question 25

Can Masking policies be applied to virtual columns?

A.FALSE

B.TRUE

Other Version: 1885Snowflake.DEA-C01.v2024-01-27.q66

Latest Upload: 212Snowflake.DEA-C01.v2026-09-04.q215; 163HP.HPE0-V27.v2026-09-04.q127; 187NAHQ.CPHQ.v2026-09-03.q481; 118SAP.C-S4CPB-2602.v2026-09-02.q7; 116Cisco.700-805.v2026-09-02.q86; 163MSSC.CLT-4.0.v2026-09-02.q43; 131Fitness.NCSF-CPT.v2026-09-02.q18; 195Google.Generative-AI-Leader.v2026-09-02.q77; 140PECB.ISO-14001-Lead-Auditor.v2026-09-01.q39; 129Google.GCP-DE.v2026-09-01.q27

Question 21

Question 22

Question 23

Question 24

Question 25

Download PDF File