In this fundamental-level course from Amazon Web Services (AWS), you learn how to assess your preparedness for the
AWS Certified Data Engineer - Associate (DEA-C01) exam. The AWS Certified Data Engineer - Associate (DEA-C01) exam validates skills and knowledge in core data-related AWS services, in the ability to implement data pipelines, to monitor and troubleshoot issues, and to optimize cost and performance in accordance with best practices.
Learn how to prepare for the exam by exploring the exam’s topic areas and how they align to developing on AWS and to specific areas of study. Gauge your understanding of topics and concepts from each task statement grouped by domain. Reinforce your knowledge and identify learning gaps with explanations of exam-style questions. Explore learning strategies to identify incorrect responses by interpreting the concepts that are being tested in the exam by using the question explanation.
For the full course, including hands-on labs and the official practice exam, see
Exam Prep Enhanced Course: AWS Certified Data Engineer - Associate (DEA-C01 - English).
Course level: Fundamental
Duration: 6 hours
Activities
This course includes the following:
- Videos by an expert instructor who delivers presentations and reviews exam-style questions.
- Hands-on exercises (builder labs) that help validate skills readiness.
- Official Practice Questions written in the same style as AWS Certification exams. All questions include detailed feedback and recommended resources to help you prepare for the exam.
Course objectives
In this course, you will do the following:
- Understand the knowledge tested by the AWS Certified Data Engineer - Associate (DEA-C01) exam.
- Evaluate your gaps in knowledge of the exam topics.
Intended audience
This course is intended for individuals who meet all of the following requirements:
- Have the equivalent of 2–3 years of experience in data engineering.
- Have 1–2 years of hands-on experience with AWS services.
- Are preparing for the AWS Certified Data Engineer - Associate (DEA-C01) exam.
Prerequisites
These are the prerequisites for the AWS Certified Data Engineer - Associate (DEA-C01) exam.
General IT knowledge
Learners should have the following IT knowledge:
- Setup and maintenance of extract, transform, and load (ETL) pipelines from ingestion to destination
- Application of high-level but language-agnostic programming concepts as required by the pipeline
- How to use Git commands for source control
- How to use data lakes to store data
- General concepts for networking, storage, and compute
Recommended AWS knowledge
Learners should have the following AWS knowledge:
- How to use AWS services to accomplish the tasks listed in the Introduction section of the exam guide
- An understanding of the AWS services for encryption, governance, protection, and logging of all data that is part of a data pipeline
- The ability to compare AWS services to understand the cost, performance, and functional differences between services
- How to structure SQL queries and how to run SQL queries on AWS services
- An understanding of how to analyze data, verify data quality, and ensure data consistency by using AWS services
Recommended courses
Although we don't require that you take any specific training before you take an exam, we do recommend that learners take the following courses (or similar courses) before taking this course:
- Data Analytics Fundamentals
- AWS Security Fundamentals (Second Edition)
- Getting Started with AWS Storage
- Introduction to AWS Identity and Access Management (IAM)
Gain hands-on experience with these resources (requires an AWS Skill Builder subscription):
- Engage in the Best of re:Invent Analytics 2022 (AWS Jam)
- AWS Cloud Quest: Data Analytics
- Performing a Basic Audit of Your AWS Environment
- Introduction to AWS Identity and Access Management (IAM) (self-paced lab)
Get to know AWS services and best practices by exploring AWS whitepapers, FAQs, and documentation relevant to your exam:
- Analytics on AWS
- Architecture Best Practices for Analytics & Big Data
- Big Data Analytics Options on AWS
- Data Residency: AWS Policy Perspectives
- Data Analytics Lens
Course outline
Module 1: Get to know the exam
- Introduction to AWS Certified Data Engineer - Associate (DEA-C01)
- Overview: AWS Certified Data Engineer - Associate (DEA-C01)
- Exam guide: AWS Certified Data Engineer - Associate (DEA-C01)
- Data engineering fundamentals
Module 2: Get to know exam-style questions
- Introduction to exam-style questions
- Overview and Instructions: Official Practice Question Set
- AWS Certified Data Engineer - Associate Official Practice Exam (DEA-C01 - English)
Module 3: Learn about exam topics
- AWS training suggestions
- Whitepapers and FAQs
Module 4: Prepare for the exam
Domain 1: Data Ingestion and Transformation
- Domain 1 introduction
- Lesson 1: Perform data ingestion
- Lesson 2: Transform and process data
- Lesson 3: Orchestrate data pipelines
- Lesson 4: Apply programming concepts
- Walkthrough question 1
- Walkthrough question 2
- Additional resources
Domain 2: Data Store Management
- Domain 2 introduction
- Lesson 1: Choose a data store
- Lesson 2: Understand data cataloging systems
- Lesson 3: Manage the lifecycle of data
- Lesson 4: Design data models and schema evolution
- Walkthrough question 3
- Walkthrough question 4
- Additional resources
Domain 3: Data Operations and Support
- Domain 3 introduction
- Lesson 1: Automate data processing by using AWS services
- Lesson 2: Analyze data by using AWS services
- Lesson 3: Maintain and monitor data pipelines
- Lesson 4: Ensure data quality
- Walkthrough question 5
- Walkthrough question 6
- Additional resources
Domain 4: Data Security and Governance
- Domain 4 introduction
- Lesson 1: Apply authentication mechanisms
- Lesson 2: Apply authorization mechanisms
- Lesson 3: Ensure data encryption and masking
- Lesson 4: Prepare logs for audit
- Lesson 5: Understand data privacy and governance
- Walkthrough question 7
- Walkthrough question 8
- Additional resources
Module 5: Register for the exam
Module 6: Course close
Module 7: Course survey
