Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 804 discussion

Exam question from Amazon's AWS Certified Solutions Architect - Associate SAA-C03

Question #: 804
Topic #: 1

[All AWS Certified Solutions Architect - Associate SAA-C03 Questions]

A company has an Amazon S3 data lake. The company needs a solution that transforms the data from the data lake and loads the data into a data warehouse every day. The data warehouse must have massively parallel processing (MPP) capabilities.

Data analysts then need to create and train machine learning (ML) models by using SQL commands on the data. The solution must use serverless AWS services wherever possible.

Which solution will meet these requirements?

A. Run a daily Amazon EMR job to transform the data and load the data into Amazon Redshift. Use Amazon Redshift ML to create and train the ML models.
B. Run a daily Amazon EMR job to transform the data and load the data into Amazon Aurora Serverless. Use Amazon Aurora ML to create and train the ML models.
C. Run a daily AWS Glue job to transform the data and load the data into Amazon Redshift Serverless. Use Amazon Redshift ML to create and train the ML models.
D. Run a daily AWS Glue job to transform the data and load the data into Amazon Athena tables. Use Amazon Athena ML to create and train the ML models.

Show Suggested Answer

Suggested Answer: C 🗳️

by asdfcdsxdfc at March 5, 2024, 10:40 p.m.

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Mikado211

Highly Voted 1 year, 5 months ago

Selected Answer: C

Data warehouse ==> Redshift Without additional informations both EMR and Glue Jobs can work. Since the question asks to use serverless as much as possible, Redshift Serverless is a better solution. C

upvoted 6 times

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BatVanyo

Highly Voted 1 year, 4 months ago

Selected Answer: C

Neither A, nor B explicitly say "EMR serverless" which is a new AWS offering, so I exclude these two. MPP goes hand in hand with Redshift, so D is also incorrect. This leaves C the only possible serverless option here.

upvoted 5 times

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ln2718

Most Recent 2 weeks, 4 days ago

Selected Answer: A

Gemini AI answer is - A - For massively parallel processing (MPP) capabilities, Amazon EMR generally offers more robust and flexible options than AWS Glue. Then use Redshift serverless for the rest.

upvoted 1 times

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sk1974

5 months, 3 weeks ago

Selected Answer: B

Any reason it cannot be B ?

upvoted 2 times

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mk168898

10 months ago

Selected Answer: C

Data Warehouse => redshift Use AWS Services whereever possible => Redshift serverless

upvoted 2 times

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rondelldell

1 year, 4 months ago

A Amazon EMR Serverless is a deployment option for Amazon EMR that provides a serverless runtime environment. This simplifies the operation of analytics applications that use the latest open-source frameworks, such as Apache Spark and Apache Hive. With EMR Serverless, you don’t have to configure, optimize, secure, or operate clusters to run applications with these frameworks. EMR Serverless helps you avoid over- or under-provisioning resources for your data processing jobs. EMR Serverless automatically determines the resources that the application needs, gets these resources to process your jobs, and releases the resources when the jobs finish. For use cases where applications need a response within seconds, such as interactive data analysis, you can pre-initialize the resources that the application needs when you create the application.

upvoted 2 times

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