DAS-C01 · Question #11
A large company has a central data lake to run analytics across different departments. Each department uses a separate AWS account and stores its data in an Amazon S3 bucket in that account. Each…
The correct answer is C. Set up an individual AWS account for the central data lake. Use AWS Lake Formation to catalog. Setting up a central AWS account and using AWS Lake Formation (Option C) is the optimal solution for meeting both access patterns with minimal administrative overhead. Lake Formation enables centralized governance across multiple AWS accounts and S3 buckets without requiring…
Question
A large company has a central data lake to run analytics across different departments. Each department uses a separate AWS account and stores its data in an Amazon S3 bucket in that account. Each AWS account uses the AWS Glue Data Catalog as its data catalog. There are different data lake access requirements based on roles. Associate analysts should only have read access to their departmental data. Senior data analysts can have access in multiple departments including theirs, but for a subset of columns only. Which solution achieves these required access patterns to minimize costs and administrative tasks?
Options
- AConsolidate all AWS accounts into one account.
- BKeep the account structure and the individual AWS Glue catalogs on each account.
- CSet up an individual AWS account for the central data lake. Use AWS Lake Formation to catalog
- DSet up an individual AWS account for the central data lake and configure a central S3 bucket.
How the community answered
(22 responses)- A18% (4)
- B9% (2)
- C68% (15)
- D5% (1)
Explanation
Setting up a central AWS account and using AWS Lake Formation (Option C) is the optimal solution for meeting both access patterns with minimal administrative overhead. Lake Formation enables centralized governance across multiple AWS accounts and S3 buckets without requiring data movement. It supports fine-grained access controls including column-level security (needed for senior analysts who can access only a subset of columns) and cross-account data sharing through AWS Resource Access Manager (RAM). It integrates natively with AWS Glue, Athena, and Redshift Spectrum. Option A requires consolidating all data into one account - a major organizational and operational disruption. Option B retains fragmented catalogs, making cross-account column-level access management very complex and error-prone. Option D would require copying data into a single central S3 bucket, creating data duplication and storage costs.
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