Q40 — AWS SAA-C03 Ch.3

Question 40 of 65 | ← Chapter 3

Q170. An online retail company has more than 50 million active customers and receives more than 25,000 orders each day. The company collects purchase data for customers and stores this data in Amazon S3.Additional customer data is stored in Amazon RDS.The company wants to make all the data available to various teams so that the teams can perform analytics. The solution must provide the ability to manage fine-grained permissions for the data and must minimize operational overheadWhich solution will meet these requirements?

Correct Answer: 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

Explanation

To meet the requirement of making all customer data available to various teams for analytics, managing fine-grained permissions, and minimizing operational overhead for an online retail company with more than 50 million active customers and more than 25,000 orders per day, a solutions architect should create a data lake using AWS Lake Formation. An AWS Glue JDBC connection can be created to Amazon RDS, and the S3 bucket can be registered in Lake Formation. Access controls can then be applied to limit access. Therefore, option C is the correct answer.Option A suggests migrating the purchase data to write directly to Amazon RDS and using RDS access controls to limit access. This approach could work but would require significant changes to the application architecture and database schema.Option B suggests scheduling an AWS Lambda function to periodically copy data from Amazon RDS to Amazon S3, creating an AWS Glue crawler, and using Amazon Athena to query the data with S3 policies to limit access. This approach could work but requires more manual configuration and may not be as scalable or cost-effective as using a data lake solution.Option D suggests creating an Amazon Redshift cluster and scheduling an AWS Lambda function to periodically copy data from Amazon S3 and Amazon RDS to Amazon Redshift, using Amazon Redshift access controls to limit access. While this approach could work, it requires more manual configuration and may not be as cost-effective or scalable as using a data lake solution.Using AWS Lake Formation provides a serverless, fully managed, and scalable solution for building a data lake on Amazon S3 and integrating with other AWS services such as Amazon RDS. With Lake Formation, fine-grained access controls can be applied to data sets based on users, groups, attributes, and conditions. This approach provides a highly secure, robust, and cost-effective solution for managing large amounts of data while minimizing administrative overhead.