Exam AWS Certified Data Analytics - Specialty topic 1 question 49 discussion

Answer is C. I have implemented federated data lake.

Correct answer is C as AWS Data Lake Formation can help provide a centralized place for maintaining data catalog to various locations, without moving the data. Also, AWS Lake Formation permissions can help provide a central access control location. Option A is wrong as consolidating accounts would increase administrative tasks. Option B is wrong as although it might work, it is more simpler to use AWS Lake Formation for access control. Option D is wrong as moving all the data to central S3 would duplicate the storage cost and increase administrative tasks.

accounts consolidation has a big administrative effort... then A is discarded... B works but doesn't have permission requirements for an analyst role... then B is discarded... if we talk about fine-grained access control and the strong power of data catalog, lake formation always is the better option... not expansive and easy to use... a central bucket is a big administrative effort and increases storage costs due to data storage duplication... then D is discarded... C any througs?

C: I passed the test

Seems to be Data Lake Formation Simplified data lake setup: Streamlines creation and configuration of a centralized data lake. Fine-grained access control: Enables table and column-level permissions for users and groups. Data cataloging and discovery: Facilitates a searchable, centralized data catalog using AWS Glue. Data transformation: Supports ETL jobs to clean, enrich, and prepare data for analysis. Integration with AWS services: Seamlessly connects with various AWS analytics and processing tools. Security and compliance: Ensures data encryption, monitors access, and provides audit logs.

Answer is C A-Move all data means cost and lot of effort B-It works but Lakeformation is easy C-Answer D- Move all data means cost and lot of effort

Option C is incorrect because it requires setting up an individual AWS account for the central datalake. This would be an unnecessary expense. It also requires using AWS Lake Formation to catalog the cross-account locations. This would be a time-consuming and expensive process. AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. It simplifies and automates many of the complex manual steps required to create a data lake, including collecting, cleaning, and cataloging data. You can use AWS Lake Formation to create a central data catalog that is accessible to all departments. You can use Lake Formation permissions to add fine-grained access controls to allow senior analysts to view specific tables and columns. However, setting up an individual AWS account for the central datalake would be an unnecessary expense. It would also require additional administrative overhead to manage the different accounts.

Option B, keeps the account structure and the individual AWS Glue catalogs on each account, but still allows for a centralized catalog using AWS Glue. It uses cross-account access for AWS Glue crawlers to scan the data in each departmental S3 bucket and identify the schema, which populates the central catalog. The senior data analysts can be added to the central account with highly detailed access controls in the Data Catalog and Amazon S3. This approach is more scalable and cost-effective in cases where there are many departments or AWS accounts involved. Option C is a valid solution to the problem described, but it may not be the most cost-effective and efficient one. Setting up an individual AWS account for the central data lake and using AWS Lake Formation to catalog the cross-account locations with fine-grained access controls for senior analysts is a good approach, but it may involve additional administrative tasks and costs. Additionally, modifying the bucket policy for each individual S3 bucket may be cumbersome and error-prone.

Lake Formation for such fine grained access. Also, no need to use Lake Formation BluePrint as data source is S3.

should access to the subset of columns means fine-grained access control. It can be implemented by Lake Formation, not individual S3 buckets. So the answer is C.

Selected Answer: C

Answer is C

Use AWS Lake Formation for cross account catalog and permission.

Answer should be C.

When did B say..to move the data.... isn't catalog of data and moving the data two different things?

C is the correct answer

C is the right answer