AWS DEA-C01 certification prep course with exercises and 2 full-length practice exams. Redshift, Glue, Athena, and more
InstructorFrank Kane
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This architectural diagram illustrates the DynamoDB Streams workflow, detailing how data flows from an application through a processing layer to various AWS services like Kinesis, S3, and Redshift.
This slide illustrates the data ingestion workflow for Amazon SageMaker Data Wrangler, mapping various AWS storage and database services to processing outputs.
This slide illustrates Amazon EventBridge architecture, detailing how Default, Partner, and Custom event buses route events from AWS services, SaaS partners, and custom applications.
The curriculum spans multiple domains including Storage (S3), Databases (DynamoDB, Redshift), and Analytics (Glue, Kinesis).
Instruction provides clear explanations of core data engineering concepts and service trade-offs.
One sampled review suggests that some learners reported that hands-on activities lack sufficient preparation of external data sources; these signals were recorded prior to the displayed update, and while a more recent update is listed, it remains uncertain if these specific issues were resolved.
Certain sections may contain outdated information regarding service deprecations or AWS console interfaces. Although a recent update is listed, these signals were recorded prior to that date and the update label does not prove a correction.
Practical exercises may lack the necessary prepared databases or sources to facilitate full end-to-end migrations. These signals were recorded prior to the displayed update, and while a more recent update is noted, it remains uncertain if these specific issues were resolved.
Aligns well with the target of AWS data engineering certification, though it may be too basic for highly experienced professionals.