ExamTopics Logo
Mail Us[email protected]
Menu
Amazon Discussions
exam questions

Exam AWS Certified Data Engineer - Associate DEA-C01 All Questions

View all questions & answers for the AWS Certified Data Engineer - Associate DEA-C01 exam
Go to Exam

Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 87 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01
Question #: 87
Topic #: 1
[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A retail company uses Amazon Aurora PostgreSQL to process and store live transactional data. The company uses an Amazon Redshift cluster for a data warehouse.

An extract, transform, and load (ETL) job runs every morning to update the Redshift cluster with new data from the PostgreSQL database. The company has grown rapidly and needs to cost optimize the Redshift cluster.

A data engineer needs to create a solution to archive historical data. The data engineer must be able to run analytics queries that effectively combine data from live transactional data in PostgreSQL, current data in Redshift, and archived historical data. The solution must keep only the most recent 15 months of data in Amazon Redshift to reduce costs.

Which combination of steps will meet these requirements? (Choose two.)

  • A. Configure the Amazon Redshift Federated Query feature to query live transactional data that is in the PostgreSQL database.
  • B. Configure Amazon Redshift Spectrum to query live transactional data that is in the PostgreSQL database.
  • C. Schedule a monthly job to copy data that is older than 15 months to Amazon S3 by using the UNLOAD command. Delete the old data from the Redshift cluster. Configure Amazon Redshift Spectrum to access historical data in Amazon S3.
  • D. Schedule a monthly job to copy data that is older than 15 months to Amazon S3 Glacier Flexible Retrieval by using the UNLOAD command. Delete the old data from the Redshift cluster. Configure Redshift Spectrum to access historical data from S3 Glacier Flexible Retrieval.
  • E. Create a materialized view in Amazon Redshift that combines live, current, and historical data from different sources.
Show Suggested Answer Hide Answer
Suggested Answer: A 🗳️
by GHill1982 at June 14, 2024, 8:12 p.m.
Disclaimers:
  • - ExamTopics website is not related to, affiliated with, endorsed or authorized by Amazon.
  • - Trademarks, certification & product names are used for reference only and belong to Amazon.

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
Submit Cancel
lalitjhawar
Highly Voted 9 months ago
Option A (A): Configuring Amazon Redshift Federated Query allows Redshift to directly query the live transactional data in the PostgreSQL database without needing to import it. This ensures that you can access the most recent live data efficiently. Option C (C): Scheduling a monthly job to copy data older than 15 months to Amazon S3 and then using Amazon Redshift Spectrum to access this historical data provides a cost-effective way to manage storage. This ensures that only the most recent 15 months of data are kept in Amazon Redshift, reducing storage costs. The historical data is still accessible via Redshift Spectrum for analytics queries.
upvoted 7 times
...
Palee
Most Recent 2 days, 18 hours ago
Selected Answer: D
Option A and D. Option C doesn't talk about archiving Historical data
upvoted 1 times
...
Vidhi212
3 months, 1 week ago
Selected Answer: A
The correct combination of steps is: A. Configure the Amazon Redshift Federated Query feature to query live transactional data that is in the PostgreSQL database. This feature allows Amazon Redshift to directly query live transactional data in the PostgreSQL database without moving the data, enabling seamless integration with the data warehouse. C. Schedule a monthly job to copy data that is older than 15 months to Amazon S3 by using the UNLOAD command. Delete the old data from the Redshift cluster. Configure Amazon Redshift Spectrum to access historical data in Amazon S3. This step archives older data to Amazon S3, which is more cost-effective than storing it in Redshift. Redshift Spectrum allows querying this archived data directly from S3, ensuring analytics queries can still access historical data.
upvoted 2 times
...
SambitParida
3 months, 1 week ago
Selected Answer: A
A & C. Redshift spectrum cant read from glacier
upvoted 1 times
...
rsmf
4 months, 3 weeks ago
Selected Answer: A
A & C is the best choice
upvoted 1 times
...
mohamedTR
5 months, 1 week ago
Selected Answer: A
A & C: allows exporting Redshift data to Amazon S3 and ability to frequent access
upvoted 1 times
...
HunkyBunky
9 months ago
Selected Answer: A
A / C is a best choice
upvoted 1 times
...
artworkad
9 months ago
Selected Answer: A
AC is correct. D is not correct, because Redshift Spectrum cannot read from S3 Glacier Flexible Retrieval.
upvoted 4 times
...
tgv
9 months ago
Selected Answer: A
Choice A ensures that live transactional data from PostgreSQL can be accessed directly within Redshift queries. Choice C archives historical data in Amazon S3, reducing storage costs in Redshift while still making the data accessible via Redshift Spectrum. (to Admin: I can't select multiple answers on the voting comment)
upvoted 4 times
...
GHill1982
9 months ago
Correct answer is A and C.
upvoted 2 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
exam
Someone Bought Contributor Access for:
SY0-701
London, 1 minute ago