Introduction
I recently achieved the AWS Certified: Data Engineer - Associate (DEA-C01) certification, and I’d like to share my journey, including the strategies and resources that helped me succeed. This certification is intended for individuals who perform data engineering roles and validates expertise in designing, building, and maintaining data architecture on AWS.
In this blog, I'll walk you through the exam prerequisites, content outline, and the resources I used to prepare for the DEA-C01 exam.
Exam Prerequisites
Before attempting this exam, AWS recommends:
Experience: At least two years of experience with data engineering and data analysis in the AWS cloud.
Knowledge: A solid understanding of AWS services related to data analytics and engineering, such as AWS Glue, Amazon Redshift, Amazon Kinesis, and Amazon S3.
Exam Overview
Level: Associate
Length: 180 minutes
Cost: $150 USD
Format: 65 questions, multiple choice or multiple response
Delivery Method: Pearson VUE and PSI; testing center or online proctored exam
Exam Outline
The following table lists the main content domains and their weightings. This is not an exhaustive list but provides a high-level overview of the topics covered.
| Domain | % of Exam |
| Domain 1: Design of Data Engineering Pipelines on AWS | 30% |
| Domain 2: Implementation of Data Pipelines | 25% |
| Domain 3: Security, Governance, and Monitoring | 20% |
| Domain 4: Storage and Data Management | 25% |
| Total | 100% |
How Did I Prepare?
Preparation is key to passing the DEA-C01 exam. Here are the resources and strategies that helped me:
📚 Courses I Took
"AWS Certified Data Analytics - Specialty" by A Cloud Guru: This course provides a comprehensive overview of AWS data analytics services and is an excellent starting point.
- 👉 More Information on the Course
"Data Engineering on AWS" by AWS Training and Certification: This official AWS course dives deep into the core data engineering services.
🛠️ Hands-On Projects
Theory alone isn’t enough; practical experience is crucial. Here are some hands-on projects that I worked on:
Building ETL Pipelines with AWS Glue: Practice transforming data from Amazon S3 to Amazon Redshift.
Streaming Data with Amazon Kinesis: Set up a real-time data processing pipeline.
Data Warehousing with Amazon Redshift: Implement a data warehousing solution using Redshift.
👉 My GitHub Repository contains the detailed projects and code I used.
📋 AWS Ramp-Up Guides
AWS Ramp-Up Guides provide a structured learning path. I used the "Data Analytics Ramp-Up Guide" to identify essential resources and track my progress.
👉 More Details on Ramp-Up Guides
🤝 Joining Study Groups
Being part of a study group can be incredibly beneficial. Here are a couple of study groups that helped me:
Cloud and DevOps Babies: A global community for learning and discussing cloud and DevOps topics.
Tech Study Slack: A Slack community for people studying for various tech certifications.
✍️ Practice Tests
Practice tests are a must. They simulate the actual exam environment and help identify areas that need improvement. I used the following resources:
Tutorials Dojo Practice Exams: These exams come with detailed explanations for each question, helping you understand why certain answers are correct or incorrect.
📝 Notes and Study Plan
I created a detailed study plan outlining the resources and timelines. Consistency and commitment to the plan were crucial.
Useful Study Tips and Tricks
Online Proctoring: This exam is available through online proctoring, so you can take it from the comfort of your home.
Extended Time: Non-native English speakers can request an additional 30 minutes.
Flagging Questions: Use the flagging mechanism to revisit difficult questions if you have time.
No Penalty for Guessing: There's no penalty for wrong answers, so make sure to attempt all questions.
Additional Resources
"Path to Data Engineering on AWS" by Ahmad Yasin
"AWS Certified Data Analytics - Specialty (DAS-C01)" by Cloud Academy
"AWS Big Data Specialty" by Adrian Cantrill
Conclusion
Preparing for the AWS Certified: Data Engineer - Associate exam requires a mix of theoretical knowledge, practical experience, and strategic study. By leveraging the right resources and staying committed to your study plan, you can successfully pass this exam and validate your expertise in data engineering on AWS.
Let me know your thoughts in the comments section 👇. Connect with me on LinkedIn, Twitter, and GitHub for more content and updates on my journey. Good luck with your exam preparation!
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✍️ Check out my blogs
Like, share, and follow me 🚀 for more content. Have fun and good luck! 💪