Exam AWS Certified Data Analytics - Specialty topic 1 question 95 discussion

I will go with Option B. Here Data is already there in S3 bucket in parquet format. We just need to register the S3 bucket with Lake Formation after the catalogue creation. Blueprints are Ideal way if the Data has to be brought to S3 from other sources. From Lake Formation FAQ: How does Lake Formation organize my data in a data lake? A: You can use one of the blueprints available in Lake Formation to ingest data into your data lake. Lake Formation creates Glue workflows that crawl source tables, extract the data, and load it to S3. In S3, Lake Formation organizes the data for you, setting up partitions and data formats for optimized performance and cost. For data already in Amazon S3, you can register those buckets with Lake Formation to manage them. Lake Formation also crawls your data lake to maintain a data catalog and provides an intuitive user interface for you to search entities (by type, classification, attribute, or free-form text.)

Looks like 'A'. https://aws.amazon.com/blogs/big-data/building-securing-and-managing-data-lakes-with-aws-lake-formation/

https://docs.aws.amazon.com/lake-formation/latest/dg/security-permissions-example-scenario.html

B: I passed the test

It's B https://docs.aws.amazon.com/lake-formation/latest/dg/register-data-lake.html

Answer B https://docs.aws.amazon.com/lake-formation/latest/dg/register-data-lake.html

B is the right answer as per doc: You can use one of the blueprints available in Lake Formation to ingest data into your data lake. Lake Formation creates Glue workflows that crawl source tables, extract the data, and load it to S3. In S3, Lake Formation organizes the data for you, setting up partitions and data formats for optimized performance and cost. For data already in Amazon S3, you can register those buckets with Lake Formation to manage them. https://aws.amazon.com/lake-formation/faqs/ Option A is wrong as duplicating the data in AWS Lake Formation would not be the most cost-effective approach. Option C is wrong as using EMR would not be the most cost-effective approach also it would take time to set up. Option D is wrong as S3 does not provide table-based or column-based access control.

A: move data takes more effort and cost C: doesn't need EMR D: We should use Lake Formation not IAM, and IAM can't offer column level control. So I like B

A: move data takes more effort and cost C: doesn't need EMR D: We should use Lake Formation not IAM, and IAM can't offer column level control. So I like B

Option B.

Use Lake Formation for the permissions. No need to use Blueprints because all the data is already in S3. Only thing that is required to get the data into the data lake is use a Glue Crawler.

Answer: B

it's A. B is ruled out as you don't have to run crawler etc. when you are using LakeFormation. It will do everything for you

I think Answer should be B

Answer : B

A - https://docs.aws.amazon.com/lake-formation/latest/dg/how-it-works.html Lake formation can move data as well as provide granular access from its blue prints - which is mainly intended for cost effective/time efficient way to implement faster data lakes. Whereas option B is building datalake on our own. build vs buy analogy wise A will suit the question from quick turnaround point of view from deployment.

B - the data is already in S3, no need to use a blueprint to import it