Amazon MLS-C01 Exam - Topic 6 Question 13 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 13
Topic #: 6

A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day the solution has to scale automatically and be cost-effective. Also, it must be possible to explore the data using SQL.

Which storage scheme is MOST adapted to this scenario?

AStore datasets as files in Amazon S3.

BStore datasets as files in an Amazon EBS volume attached to an Amazon EC2 instance.

CStore datasets as tables in a multi-node Amazon Redshift cluster.

DStore datasets as global tables in Amazon DynamoDB.

Show Suggested Answer

Suggested Answer: A

by Jovita at May 04, 2022, 01:45 AM

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Royce

4 months ago

Not sure about D, seems like overkill for this use case.

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Tegan

4 months ago

Wait, can you really explore S3 data with SQL?

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Olene

4 months ago

I think C could work too, but not as cost-effective.

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Cassie

4 months ago

Totally agree, S3 is super flexible!

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Lucia

5 months ago

A is the best choice for scalability and cost.

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Rosendo

5 months ago

Hmm, I'm a bit unsure about this one. The requirements mention using the Internet as the underlay, so I'm not sure if S-VTI would be the right choice. I'll need to think this through carefully.

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Hildegarde

5 months ago

I'm a little confused by the options here. They all seem related to SIAM, but I'm not sure which one is the most accurate benefit. I'll have to guess and hope for the best.

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Zona

5 months ago

This seems like a pretty straightforward problem. I'd go with option C and use the Cloud Vision API with custom labels. That should give us a quick and easy solution to get the app up and running.

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Page

5 months ago

I thought the agent had to go Ready before they could even do After Call Work, but I could be mixing it up with something else.

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