Manage the lifecycle of data.

8 practice questions under this official exam objective (DEA-C01) — each with the community-verified answer, a full option-by-option explanation and instant feedback.

DEA-C01 S-grade

Which S3 Lifecycle Policy Meets High Availability and Lowest Cost?

This DEA-C01 question tests an S3 Lifecycle policy that moves aging data from S3 Standard to the cheapest storage class while preserving high availabi

36 comments
DEA-C01 S-grade

Solving Athena Query Planning Bottlenecks with Partition Indexing and Projection

This guide explains how to resolve Amazon Athena query planning bottlenecks caused by a high volume of S3 partitions using Glue partition indexing and

14 comments
DEA-C01 S-grade

S3 Intelligent-Tiering Default vs Deep Archive for Millisecond Retrieval

This page analyzes how to optimize S3 storage costs while maintaining millisecond retrieval times, establishing that the default access tier of S3 Int

12 comments
DEA-C01 S-grade

How Do You Combine Live, Current, and Archived Redshift Data?

Amazon Redshift Federated Query lets Redshift read live Aurora PostgreSQL tables without copying them, while a monthly UNLOAD job moves data older tha

10 comments
DEA-C01 S-grade

Reclaiming Storage in Amazon Redshift Materialized Views

This question addresses the correct method for reclaiming database storage space in Amazon Redshift materialized views, distinguishing between logical

7 comments
DEA-C01 A-grade

Least Effort to Monitor S3 Incomplete Uploads and Versions

AWS Storage Lens provides out-of-the-box metrics for incomplete multipart uploads and outdated object versions, offering the least operational effort

4 comments
DEA-C01 A-grade

Prevent Unintentional S3 File Deletion

Amazon S3 Versioning is the correct solution to prevent unintentional file deletion with the least operational overhead. It automatically retains mult

4 comments
DEA-C01 A-grade

Optimize Redshift Spectrum Query Performance with Columnar Format and Partitioning

This question addresses optimizing Amazon Redshift Spectrum queries by leveraging columnar file formats and partitioning to reduce I/O overhead. It es

3 comments