Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 204 discussion

Answer : C keyword "manage-fine-grained" https://aws.amazon.com/blogs/big-data/manage-fine-grained-access-control-using-aws-lake-formation/

With Lake formation you can scale permissions more easily with fine-grained security capabilities, including row- and cell-level permissions and tag-based access control.

Answer is C

Keyword: "manage fine-grained permissions for data" Data Lake Using Lake Formation: manage fine-grained permissions for the data with ease. Fine grained permissions for data = Lake Formation Answer: C

C represents the easiest way to ingest data from S3 and control accesses.

a fine grained permissons is one of the conditions to acomplishes with the requirement. With the use of AWS Glue you can get acomplishes with this requirement. My answer is: C

Lake Formation enables the creation of a secure and scalable data lake on AWS, allowing centralized access controls for both S3 and RDS data. By using Lake Formation, the company can manage permissions effectively and integrate RDS data through the AWS Glue JDBC connection. Registering the S3 in Lake Formation ensures unified access control. This solution reduces operational overhead while providing fine-grained permissions management.

Lake Formation enables the creation of a secure and scalable data lake on AWS, allowing centralized access controls for both S3 and RDS data. By using Lake Formation, the company can manage permissions effectively and integrate RDS data through the AWS Glue JDBC connection. Registering the S3 in Lake Formation ensures unified access control. This solution reduces operational overhead while providing fine-grained permissions management. A. Directly writing purchase data to Amazon RDS with RDS access controls lacks comprehensive permissions management for both S3 and RDS data. B. Periodically copying data from RDS to S3 using Lambda and using AWS Glue and Athena for querying does not offer fine-grained permissions management and introduces data synchronization complexities. D. Creating an Redshift cluster and copying data from S3 and RDS to Redshift adds complexity and operational overhead without the flexibility of Lake Formation's permissions management capabilities.

Answer is C AWS Lake Formation provides a comprehensive solution for building and managing a data lake. It simplifies data ingestion, organization, and access control. By creating a data lake using AWS Lake Formation, you can centralize and govern access to your data across multiple sources.

Option C is right answer: https://docs.aws.amazon.com/lake-formation/latest/dg/what-is-lake-formation.html

Lake Formation helps you manage fine-grained access for internal and external customers from a centralized location and in a scalable way.

https://docs.aws.amazon.com/lake-formation/latest/dg/access-control-overview.html

To me, the give-away was: "The company wants to make all the data available to various teams" - Data-Lake - All data in one place.

The correct answer is D. The company uses all the data from various teams so that the teams can do their analysis. Therefore, it is the best way to separately configure redshift for data warehousing and for all employees to connect to the redshift DB and perform analysis tasks without burdening the operating DB (must minimize operational overhead).

Manage fine-grained access control using AWS Lake Formation https://aws.amazon.com/blogs/big-data/manage-fine-grained-access-control-using-aws-lake-formation/

Option C. Create a data lake by using AWS Lake Formation. Create an AWS Glue JDBC connection to Amazon RDS. Register the S3 bucket in Lake Formation. Use Lake Formation access controls to limit access. To make all the data available to various teams and minimize operational overhead, the company can create a data lake by using AWS Lake Formation. This will allow the company to centralize all the data in one place and use fine-grained access controls to manage access to the data. To meet the requirements of the company, the solutions architect can create a data lake by using AWS Lake Formation, create an AWS Glue JDBC connection to Amazon RDS, and register the S3 bucket in Lake Formation. The solutions architect can then use Lake Formation access controls to limit access to the data. This solution will provide the ability to manage fine-grained permissions for the data and minimize operational overhead.

a combination of the following 2 URLs I believe it is C https://aws.amazon.com/lake-formation/ https://aws.amazon.com/blogs/big-data/manage-fine-grained-access-control-using-aws-lake-formation/