Data Engineer Associate Practice Tests (DEA-C01)

Data Engineer Associate Practice Tests (DEA-C01) is the essential practice examination suite for candidates pursuing the AWS Certified Data Engineer – Associate (DEA-C01) certification. This certification validates the specialized skills required to design, implement, and monitor data pipelines on AWS using services like S3, Glue, EMR, Redshift, and Kinesis. The DEA-C01 exam focuses on the practical application of data engineering principles, covering ingestion, transformation, data modeling, and governance in the context of the AWS Data Lake. Our practice tests are meticulously engineered to simulate the technical and pipeline-focused challenges of the official exam.

The Data Engineer Associate role is critical for building scalable data platforms. Our simulations cover the four core skill domains: Data Ingestion and Transformation, Data Store Management, Data Governance and Quality, and Monitoring and Operationalization. You will face challenging questions involving crucial data engineering tasks, such as optimizing ETL/ELT jobs with AWS Glue and Spark, designing data lake storage structures in S3, selecting the right analytical database (Redshift, Aurora, DynamoDB), and implementing real-time data streaming solutions using Kinesis. The questions emphasize the practical trade-offs between cost, latency, and throughput.

Each practice test is a full-length, timed simulation, which is essential for building speed and precision. Upon completion, you receive immediate, comprehensive feedback with detailed, expert-written explanations for every question. These explanations provide the pipeline rationale, code examples (e.g., Glue/Spark configurations), and best practices for data lake implementation. This course is continuously updated to align with the latest AWS data services and the DEA-C01 exam objectives. By mastering these simulations, you will prove your technical expertise as a certified AWS Data Engineer.

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What Will Students Learn in Your Course?<

* Master the design and implementation of batch and streaming data ingestion pipelines using AWS Glue and Kinesis.

* Design and optimize data store management using S3 for the Data Lake and specialized databases like Redshift.

* Implement data governance and quality controls, including cataloging (Glue Data Catalog) and access control (Lake Formation).

* Configure and manage monitoring and operationalization of data pipelines using CloudWatch and other tools.

* Understand data modeling techniques for both transactional and analytical workloads.

What Are the Requirements or Prerequisites for Taking Your Course?

* One or more years of hands-on experience in a data engineering role.

* Proficiency in SQL and at least one programming language used for data processing (Python or Scala).

* Experience with ETL/ELT and data warehousing concepts.

Who Is This Course For?

* Data Engineers, ETL Developers, and BI/Data Warehouse Specialists.

* Individuals seeking the AWS Certified Data Engineer – Associate (DEA-C01) certification.

* Anyone responsible for building and maintaining data pipelines on AWS.