Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

AWS Lake Formation is a service that helps you build, secure, and manage data lakes on Amazon S3. You can use AWS Lake Formation to register the S3 path as a data lake location, and enable fine-grained access control to limit access to the records based on the HR department’s Region. You can use data filters to specify which S3 prefixes or partitions each HR department can access, and grant permissions to the IAM roles of the HR departments accordingly. This solution will meet the requirement with the least operational overhead, as it simplifies the data lake management and security, and leverages the existing IAM roles of the HR departments12.

The other options are not optimal for the following reasons:

A. Use data filters for each Region to register the S3 paths as data locations. This option is not possible, as data filters are not used to register S3 paths as data locations, but to grant permissions to access specific S3 prefixes or partitions within a data location. Moreover, this option does not specify how to limit access to the records based on the HR department’s Region.

C. Modify the IAM roles of the HR departments to add a data filter for each department’s Region. This option is not possible, as data filters are not added to IAM roles, but to permissions granted by AWS Lake Formation. Moreover, this option does not specify how to register the S3 path as a data lake location, or how to enable fine-grained access control in AWS Lake Formation.

E. Create a separate S3 bucket for each Region. Configure an IAM policy to allow S3 access. Restrict access based on Region. This option is not recommended, as it would require more operational overhead to create and manage multiple S3 buckets, and to configure and maintain IAM policies for each HR department. Moreover, this option does not leverage the benefits of AWS Lake Formation, such as data cataloging, data transformation, and data governance.

1: AWS Lake Formation

2: AWS Lake Formation Permissions

AWS Identity and Access Management

Amazon S3

The problem described requires identifying matching records even when there is no unique identifier. AWS Lake Formation FindMatches is designed for this purpose. It uses machine learning (ML) to deduplicate and find matching records in datasets that do not share a common identifier.

D. Train and use the AWS Lake Formation FindMatches transform in the ETL job:

FindMatches is a transform available in AWS Lake Formation that uses ML to discover duplicate records or related records that might not have a common unique identifier.

It can be integrated into an AWS Glue ETL job to perform deduplication or matching tasks.

FindMatches is highly effective in scenarios where records do not share a key, such as customer records from different sources that need to be merged or reconciled.

 AWS Glue is a fully managed serverless ETL service that can handle data deduplication with minimal operational overhead. AWS Glue provides a built-in ML transform called FindMatches, which can automatically identify and group similar records in a dataset. FindMatches can also generate a primary key for each group of records and remove duplicates. FindMatches does not require any coding or prior ML experience, as it can learn from a sample of labeled data provided by the user. FindMatches can also scale to handle large datasets and optimize the cost and performance of the ETL job. References:

AWS Glue

FindMatches ML Transform

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide