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

AWS Database Migration Service (AWS DMS) is a service that helps you migrate databases to AWS quickly and securely. You can use AWS DMS to migrate the Hive metastore from the on-premises Hadoop clusters into Amazon S3, which is a highly scalable, durable, and cost-effective object storage service. AWS Glue Data Catalog is a serverless, managed service that acts as a central metadata repository for your data assets. You can use AWS Glue Data Catalog to scan the Amazon S3 bucket that contains the migrated Hive metastore and create a data catalog that is compatible with Apache Hive and other AWS services. This solution meets the requirements of migrating the data catalog into a persistent storage solution and using a serverless solution. This solution is also the most cost-effective, as it does not incur any additional charges for running Amazon EMR or Amazon Aurora MySQL clusters. The other options are either not feasible or not optimal. Configuring a Hive metastore in Amazon EMR (option B) or an external Hive metastore in Amazon EMR (option C) would require running and maintaining Amazon EMR clusters, which would incur additional costs and complexity. Using Amazon Aurora MySQL to store the company’s data catalog (option C) would also incur additional costs and complexity, as well as introduce compatibility issues with Apache Hive. Configuring a new Hive metastore in Amazon EMR (option D) would not migrate the existing data catalog, but create a new one, which would result in data loss and inconsistency. References:

Using AWS Database Migration Service

Populating the AWS Glue Data Catalog

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 4: Data Analysis and Visualization, Section 4.2: AWS Glue Data Catalog

Option A minimizes administration because it keeps one base IAM role for the pipeline and enforces regional locality at session time by attaching a session policy when the broker calls AssumeRole. This aligns with the security best practice of applying only what is necessary, because permissions should be limited to the exact scope required for the session. The material explicitly emphasizes the principle of least privilege, stating that permissions “should apply only to what is necessary,” and the most appropriate approach is to grant only the minimum actions needed for the job.

With session policies, the organization avoids creating and maintaining separate per-Region roles (Option B), avoids managing users and group memberships for federated sessions (Option C), and avoids individually attaching policies per engineer (Option D). Instead, the broker can dynamically apply a Region-specific restriction for each login, ensuring the temporary credentials are valid only for the engineer’s working Region. This design reduces ongoing operational burden while still enforcing strict locality controls through temporary, scoped credentials and least-privilege boundaries.

Amazon S3 natively supports checksum validation during uploads when objects are uploaded by using the AWS SDK. The SDK can automatically calculate a checksum, such as CRC32, on the client side and send it with the upload request. Amazon S3 validates the checksum upon receipt and stores it with the object, ensuring that the data uploaded is exactly the same as the source data.

Storing the checksum in the S3 object metadata provides a lightweight and cost-effective way to verify data integrity without requiring additional compute, storage, or post-processing steps. This approach validates the logs at upload time, which is the most efficient and reliable method.

Using AWS Lambda to calculate SHA-256 checksums would require additional compute, orchestration, and storage, increasing cost and operational complexity. Amazon S3 Object Lock enforces immutability and retention but does not validate data integrity between source and destination. Governance or compliance mode Object Lock cannot detect whether uploaded data matches the original logs.

Therefore, using the AWS SDK checksum validation during upload is the simplest, most efficient, and AWS-recommended approach for ensuring log integrity.