The DEA-C01 exam for AWS Certified Data Engineer - Associate assesses a candidate's proficiency in implementing data pipelines and addressing cost and performance concerns following best practices. The exam covers various tasks, including:

1. Ingesting and transforming data, orchestrating data pipelines, and applying programming concepts.

2. Selecting optimal data stores, designing data models, cataloging data schemas, and managing data lifecycles.

3. Operationalizing, maintaining, and monitoring data pipelines, as well as analyzing data and ensuring data quality.

4. Implementing authentication, authorization, data encryption, privacy, and governance, including enabling logging.

Recommended general IT knowledge includes setting up and maintaining extract, transform, and load (ETL) pipelines, applying high-level programming concepts, using Git commands for source control, understanding data lakes, and having a grasp of networking, storage, and compute concepts.

AWS-specific knowledge should cover using AWS services for the listed tasks, understanding AWS services for encryption, governance, protection, and logging, comparing AWS services for cost, performance, and functionality differences, structuring and running SQL queries on AWS services, and analyzing data for quality and consistency using AWS services.

Tasks outside the scope of the exam include performing artificial intelligence and machine learning tasks, demonstrating programming language-specific syntax knowledge, and drawing business conclusions based on data.

The exam comprises multiple-choice and multiple-response questions, with unscored questions included for performance evaluation. A passing score is 720, and results are reported on a scaled score of 100–1,000, reflecting overall performance. The exam uses a compensatory scoring model, meaning passing in each section is not required, and section weights vary.

Content domains and weightings for the exam include:

1. Data Ingestion and Transformation (34%)

2. Data Store Management (26%)

3. Data Operations and Support (22%)

4. Data Security and Governance (18%)