Hello, and welcome to this course, which has been designed to help you prepare for and pass the AWS Certified Data Engineer - Associate certification exam.

My name is Danny Jessee, and I am one of the trainers here at Cloud Academy, specializing in AWS–Amazon Web Services–and AWS certifications. Feel free to connect with me to ask any questions using the details shown on the screen. Alternatively, you can always get in touch with us here at Cloud Academy by sending an email to support@cloudacademy.com, where one of our cloud experts will reply to your question.

The AWS Certified Data Engineer - Associate is a new associate-level certification that’s designed for those in a data engineering role who have hands-on experience using AWS services to set up and maintain extract, transform, and load, or ETL pipelines. In order to do this, you should know how to ingest and transform data, design data models and schemas, and implement proper security, including authentication, authorization, and encryption. This course will provide you with the knowledge you need when preparing to take the AWS Certified Data Engineer - Associate certification exam, which has exam code DEA-C01.

The certification itself is broken down into four distinct domains:

Data Ingestion and Transformation (34%),
Data Store Management (26%),
Data Operations and Support (22%), and
Data Security and Governance (18%).

Each of these domains carry a specific percentage weighting within the exam. Each domain also contains a series of task statements that call out specific required knowledge and skills. These are outlined in the official AWS exam guide, which can be found here. Let’s start by taking a look at each of these domains in more detail to give you a better understanding of the topics that will be covered on the exam.

We’ll begin with Domain 1: Data Ingestion and Transformation. This domain accounts for 34% of the exam content and focuses on four task statements:

Perform data ingestion,
Transform and process data,
Orchestrate data pipelines, and
Apply programming concepts.

This domain will test your knowledge of ETL fundamentals, specifically the process of ingesting data and then transforming it to facilitate further processing. This involves understanding the concepts of volume, velocity, and variety of data, and differences you’ll need to take into account when dealing with structured versus unstructured data. You should know how to use services like Amazon Kinesis when you have a requirement to read streaming data. It’s especially important to have an understanding of how services like Amazon EMR and AWS Glue can be used to read and perform transformations on data from batch sources. When it comes to orchestrating pipelines, you should have a general understanding of services like EventBridge and AWS Step Functions, and know how they can be used to build ETL workflows for your data pipelines.

Next, we have Domain 2: Data Store Management. This domain accounts for 26% of the exam content and focuses on these four task statements:

Choose a data store,
Understand data cataloging systems,
Manage the lifecycle of data, and
Design data models and schema evolution.

This domain will assess your understanding of data storage formats, platforms, and services. You should be able to analyze a set of cost and performance requirements to determine the most appropriate data store to use in a given scenario. For instance, you may need to leverage Amazon S3 as a data store for objects stored in Parquet format to be queried by Amazon Athena. You may need to implement a data lake using AWS Lake Formation, or a data warehouse with Amazon Redshift. For more traditional relational and non-relational databases, you’ll need to consider Amazon RDS or DynamoDB. And when it comes to managing data lifecycles, you should understand how to leverage features such as S3 lifecycle policies or TTL in DynamoDB. In terms of schema evolution, you’ll need to understand how to leverage tools such as the AWS Schema Conversion Tool to design and evolve data schemas, or Amazon SageMaker ML Lineage Tracking to establish data lineage.

After that, we have Domain 3: Data Operations and Support. This domain accounts for 22% of the exam content and also has four task statements:

Automate data processing by using AWS services,
Analyze data by using AWS services,
Maintain and monitor data pipelines, and
Ensure data quality.

This domain will test your knowledge of the day-to-day operations, maintenance, and troubleshooting of data pipelines. This could involve the use of AWS Glue DataBrew for anything from preparing data transformation to visualizing data to defining data quality rules and investigating data consistency issues. You should know how Amazon Macie can be used to identify potentially sensitive data that’s stored in S3. And when it comes to monitoring, you’ll need to understand how Amazon CloudWatch and AWS CloudTrail are used for logging, log analysis, and tracking of API calls.

Finally, we have Domain 4: Data Security and Governance. This domain accounts for 18% of the exam content and assesses you based on five task statements:

Apply authentication mechanisms,
Apply authorization mechanisms,
Ensure data encryption and masking,
Prepare logs for audit, and
Understand data privacy and governance.

This final domain is all about your understanding and awareness of how to secure your data pipelines and implement appropriate governance controls to ensure data integrity, privacy, and compliance. For authentication and authorization, you’ll need to know how to use AWS Identity and Access Management, including IAM groups, roles, and policies, to define and control access to your AWS resources. For data encryption, you should understand how the AWS Key Management Service is used to create and manage the keys that are used to encrypt and decrypt your data. And when it comes to maintaining governance, you should be able to use services like AWS Config to track and manage configuration changes within an AWS account.

Throughout this course, you will be guided through a series of lessons, hands-on labs, and assessments that cover every element within the domains I just discussed. This will ensure that you have the required knowledge and sufficient understanding to enable you to pass this certification exam.

Feedback on our courses here at Cloud Academy is valuable to both us as trainers and any students looking to take the same course in the future. If you have any feedback, positive or negative, or if you notice anything that needs to be updated or corrected for the next release cycle, it would be greatly appreciated if you could email support@cloudacademy.com.

That brings me to the end of this introduction, now let’s dive in! Best of luck on your certification journey!

DEA-C01 Course Introduction

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