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Amazon Exam DAS-C01 Topic 2 Question 97 Discussion

Actual exam question for Amazon's DAS-C01 exam

Question #: 97
Topic #: 2

[All DAS-C01 Questions]

A company wants to use a data lake that is hosted on Amazon S3 to provide analytics services for historical dat

a. The data lake consists of 800 tables but is expected to grow to thousands of tables. More than 50 departments use the tables, and each department has hundreds of users. Different departments need access to specific tables and columns.

Which solution will meet these requirements with the LEAST operational overhead?

ACreate an 1AM role for each department. Use AWS Lake Formation based access control to grant each 1AM role access to specific tables and columns. Use Amazon Athena to analyze the data.

BCreate an Amazon Redshift cluster for each department. Use AWS Glue to ingest into the Redshift cluster only the tables and columns that are relevant to that department. Create Redshift database users. Grant the users access to the relevant department's Redshift cluster. Use Amazon Redshift to analyze the data.

CCreate an 1AM role for each department. Use AWS Lake Formation tag-based access control to grant each 1AM role
access to only the relevant resources. Create LF-tags that are attached to tables and columns. Use Amazon Athena to analyze the data.

DCreate an Amazon EMR cluster for each department. Configure an 1AM service role for each EMR cluster to access

Erelevant S3 files. For each department's users, create an 1AM role that provides access to the relevant EMR cluster. Use Amazon EMR to analyze the data.

Show Suggested Answer

Suggested Answer: C

by Arlean at Jul 06, 2024, 11:52 AM

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Junita

4 months ago

Option A looks good, but I'm worried about the scalability. 800 tables now, but thousands later? IAM roles could get unwieldy.

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Martina

4 months ago

Haha, Option D is like setting up a whole new theme park just for each department. Talk about operational overhead!

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Yvonne

3 months ago

D: Yeah, Option D does seem like a lot of work. Option A is definitely the way to go for this scenario.

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Raelene

3 months ago

C: Option A definitely minimizes operational overhead compared to creating separate clusters for each department.

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Gilma

4 months ago

B: I agree, Option A seems like the best choice for managing access to the data lake.

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Veronika

4 months ago

A: Option A sounds like the most efficient solution. Each department gets specific access without creating separate clusters.

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Lili

5 months ago

I'm not sure about Option B. Creating a separate Redshift cluster for each department could get expensive and complex to manage.

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Lilli

5 months ago

I see your point, Ceola. Option C also offers tag-based access control, which can simplify management as the number of tables increases.

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Annice

5 months ago

Option C seems like the most efficient solution. Using tag-based access control will make it easy to manage permissions as the data lake grows.

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Lashawn

4 months ago

I agree. It's important to have a scalable solution in place for future growth.

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Tess

5 months ago

Option C seems like the most efficient solution. Using tag-based access control will make it easy to manage permissions as the data lake grows.

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Ceola

5 months ago

But with option A, we can use AWS Lake Formation for access control, which is more scalable as the data lake grows.

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Kasandra

5 months ago

I disagree, I believe option B is more efficient. Creating separate Redshift clusters for each department ensures data isolation.

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Ceola

5 months ago

I think option A is the best choice. It allows for specific access control for each department.

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