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The AWS Certified Data Engineer Associate (DEA-C01) is the latest addition to the portfolio of AWS certifications.
This intermediate-level certification confirms expertise in fundamental AWS services related to data, along with the skills to construct data pipelines, oversee and rectify problems, and enhance both cost-efficiency and performance in accordance with established best practices.
In this article you’ll learn what this new exam is, who it is for, and how you can best prepare to pass this challenging exam.
This guide includes the following topics:
- AWS Certified Data Engineer – Associate – Exam Overview
- Which services and skills are included?
- Top 10 AWS Services on the Exam
- Top 10 Data Engineering-Specific Skills on the Exam
- How difficult is the exam?
- How can I best prepare?
AWS Certified Data Engineer – Associate – Exam Overview
At the time of writing, only the beta exam is currently available so this article focuses on the details of this exam.
The following table summarizes the key information about the beta DEA-C01 exam:
Number of questions
Multiple choice and multiple response
720 points out of 1000
Tip: The final exam may vary in length, difficulty, and even subject matter. It is likely that the final exam will be 65 questions, 130 minutes long, and will cost $150 USD. This is in line with the other associate certifications.
The exam is broken into the following 4 domains:
- Domain 1: Data Ingestion and Transformation (34% of scored content)
- Domain 2: Data Store Management (26% of scored content)
- Domain 3: Data Operations and Support (22% of scored content)
- Domain 4: Data Security and Governance (18% of scored content)
Click the image above to watch Neal’s video on the latest CLF-C01 exam updates from our youtube channel
Which services are included?
You can check the AWS exam guide for an exhaustive list of services that are included in the exam.
Knowledge requirements include a solid understanding of AWS networking concepts such as Amazon VPC, interface endpoints, routing, security groups, and AWS Transit Gateway.
There is extensive coverage of serverless solutions, so you’ll need to be familiar with event-driven architectures and AWS application integration services such as SQS, SNS, and EventBridge.
Overall, there are many services covered on the exam, so in this article I’m going to focus on the most important data engineering services and skills you MUST know to be successful in the DEA-C01 exam.
Top 10 AWS Services on the Exam
- Amazon Redshift:
- Focuses on data warehousing, query performance optimization, and data distribution strategies.
- Redshift Data API for seamless integration with other AWS services
- Redshift Spectrum, Redshift query optimizer, creating table views, and using the VACUUM command for reclaiming space and improving query performance.
- AWS Glue:
- Covers ETL processes, AWS Glue Data Catalog, crawlers, and workflows for data integration and transformation.
- Amazon S3:
- Involves data storage, lifecycle management, and integration with other AWS services for data lakes and analytics.
- You should also understand the use and application of Amazon S3 Select.
- Amazon Athena:
- Pertains to serverless querying service, performance optimization, and integration with AWS Glue and S3.
- Benefits of using certain file formats such as Apache Parquet.
- AWS Lambda:
- Includes serverless computing, event-driven data processing, and integration with services like Amazon S3 and Amazon Aurora.
- Amazon Aurora:
- Focuses on high-performance database solutions, connectivity, and integration with AWS services like Lambda.
- Amazon EMR (Elastic MapReduce):
- Covers big data processing, Apache Hadoop ecosystem, and data analysis using tools like Apache Spark and HBase.
- Amazon Kinesis:
- Involves real-time data streaming, processing, and analytics, including Kinesis Data Streams, Data Firehose, and Data Analytics.
- Amazon RDS (Relational Database Service):
- Pertains to managed relational database services, performance tuning, and integration with other AWS services for analytics.
- AWS Step Functions:
- Involves orchestration of serverless workflows, integration with AWS Lambda, and automation of ETL jobs.
- Amazon States Language (ASL) and defining states for your workflow.
Top 10 Data Engineering-Specific Skills on the Exam
To successfully pass the AWS Certified Data Engineer Associate exam, apart from proficiency in AWS services, the following top 10 skills are essential:
- Data Modeling and Database Design:
- Understanding of data normalization, schema design, and data warehousing concepts.
- Ability to design efficient and scalable database schemas for various use cases.
- SQL Proficiency:
- Strong skills in SQL for querying, data manipulation, and analysis.
- Knowledge of advanced SQL features for complex data operations.
- Programming and Scripting:
- Proficiency in programming languages like Python or Java, commonly used in data engineering.
- Ability to write, debug, and optimize code for data processing and ETL tasks.
- Data Processing and ETL Techniques:
- Understanding of ETL (Extract, Transform, Load) processes and tools.
- Skills in transforming and preparing large datasets for analysis.
- Big Data Technologies:
- Familiarity with big data ecosystems, including Hadoop, Spark, and related technologies.
- Understanding of distributed computing and data processing at scale.
- Data Security and Compliance:
- Knowledge of data security best practices, including encryption, IAM roles, and security groups.
- Awareness of compliance requirements related to data (e.g., GDPR, HIPAA).
- Performance Tuning and Optimization:
- Skills in optimizing data queries and storage for performance.
- Ability to troubleshoot and tune system performance issues.
- Data Integration and Pipeline Orchestration:
- Experience in integrating data from various sources and formats.
- Understanding of data pipeline orchestration tools and techniques.
- Cloud Networking and Architecture:
- Basic knowledge of cloud networking concepts, VPCs, network ACLs, and route tables.
- Understanding of AWS cloud architecture best practices for data engineering.
- Monitoring and Logging:
- Skills in monitoring AWS resources and applications.
- Familiarity with AWS CloudWatch and other logging and monitoring tools.
How difficult is the exam?
The AWS Certified Data Engineer Associate exam is not an easy exam. In my experience of the beta, it is much harder than the other associates. However, it’s worth noting that I am not a data engineer so some questions were outside my normal scope of work and experience.
You really do need data engineering experience to be successful in this exam, it’s not just a case of understanding the AWS services well enough (as per other associates like the DVA and SOA). For this exam, you must be familiar with data engineering practices, preferably with plenty of hands-on experience.
According to AWS, the exam is designed for candidates with 2-3 years of experience in cloud data-related roles or in on-premises data-related roles, moving to the AWS Cloud. If you have this requisite experience, then the exam may be easier for you than it was for me.
How can I best prepare?
At Digital Cloud Training, we are currently working on a practice test course for the exam, which is coming soon. We’ll also create a video-based training course ahead of the release of the final exam. In our training library, you can also find in-depth training on many of the AWS services in scope for the AWS Certified Data Engineer Associate certification.
As discussed in the YouTube video on our experience in the beta exam, be wary of any training courses released before the final exam is released (and especially those released before the beta exam was released), as these courses may not be in line with the exam. It was a surprise for us so it will be for them as well!
It is highly recommended that you pass your AWS Certified Solutions Architect Associate exam at a minimum before you attempt the DEA-C01. In addition to doing the other associate-level AWS certifications, check the AWS exam guide for the DEA-C01 and the notes above and use the AWS documentation to learn as much as possible on these topics.
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