AWS Certified Data Engineer Associate 2024 - Hands On!

Sundog Education by Frank Kane, Frank Kane, and Stephane Maarek | AWS Certified Cloud Practitioner,Solutions Architect,Developer

NEW: Now includes a full-length practice exam.

The AWS Certified Data Engineer Associate Exam (DEA-C01 or DE1-C01) is one of the most challenging associate-level certification exams you can take from Amazon Web Services, and even among the most challenging overall. Passing it tells employers in no uncertain terms that your knowledge of data pipelines is wide and deep. But, even experienced technologists need to prepare heavily for this exam. This course sets you up for success, by covering all of the data ingestion, transformation, and orchestration technologies on the exam and how they fit together.

Best-selling Udemy instructors Frank Kane and Stéphane Maarek have teamed up to deliver the most comprehensive and hands-on prep course we've seen. Together, they've taught over 2 million people around the world. This course combines Stéphane's depth on AWS with Frank's experience in wrangling massive data sets, gleaned during his 9-year career at Amazon itself.

The world of data engineering on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are:

Streaming and transforming data with Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (MSK)
Queuing messages with Simple Queue Service (SQS)
Orchestrating data pipelines with Amazon AppFlow, Amazon EventBridge, AWS Step Functions, and Amazon Managed Workflows for Apache Airflow (MWAA)
Transitioning from small to big data with the AWS Database Migration Service (DMS), AWS DataSync, Snow Family, Transfer Family, and more
Storing massive data lakes with the Simple Storage Service (S3) and managing data lifecycles
Optimizing transactional queries with DynamoDB, DocumentDB, Keyspaces, and MemoryDB
Tying your big data systems together with AWS Lambda
Making unstructured data query-able with AWS Glue, Glue DataBrew, and Lake Formation
Processing data at unlimited scale with Elastic MapReduce, including Apache Spark
Applying advanced machine learning algorithms at scale with Amazon SageMaker
Searching and analyzing petabyte-scale data with Amazon Opensearch (formerly Elasticsearch) Service
Querying S3 data lakes with Amazon Athena
Hosting massive-scale data warehouses with Redshift and Redshift Spectrum
Integrating smaller data with your big data, using the Relational Database Service (RDS)
Keeping your data secure with encryption, KMS, Macie, Secrets Manager, IAM, and more
Managing and governing your systems with CloudFormation, CloudTrail, CloudWatch, AWS Config, and more

Throughout the course, you'll have lots of opportunities to reinforce your learning with hands-on demos, a full-length practice exam, and additional practice questions. We'll also arm you with some valuable test-taking tips and strategies along the way.

Although this is an associate-level exam, it is one of the more challenging ones. AWS recommends having a few years of both data engineering experience and AWS experience before tackling it. This exam is not intended for AWS beginners.

You want to go into the AWS Certified Data Engineer Associate Exam with confidence, and that's what this course delivers. Hit the enroll button, and we're excited to see you in the course... and ultimately to see you get your certification.

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Instructor

My name is Stéphane Maarek, I am passionate about Cloud Computing, and I will be your instructor in this course. I teach about AWS certifications, focusing on helping my students improve their professional proficiencies in AWS.

I have already taught

With AWS becoming the centerpiece of today's modern IT architectures, I have decided it is time for students to learn how to be an AWS Data Analytics Professional. So, let’s kick start the course. You are in good hands.

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Instructor

Hey, I'm Frank Kane, and I'm also co-instructing this course. I spent nine years working for Amazon from the inside as a senior engineer and senior manager, and I'm best known for my top-selling courses in "big data", data analytics, machine learning, AI, Apache Spark, system design, and Elasticsearch.

I've been teaching on Udemy since 2015, where I've reached over 800,000 students all around the world.

I've worked hard to keep this course up to date with the latest developments in AWS data engineering, and to make sure you're prepared for the latest version of this exam. Let's dive in and get you ready.

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This course also comes with:

Lifetime access to all future updates
A responsive instructor in the Q&A Section
Udemy Certificate of Completion Ready for Download
A 30 Day "No Questions Asked" Money Back Guarantee.

Join us in this course if you want to pass the AWS Certified Data Engineer - Associate Exam DEA-C01 and master the AWS platform.

Enroll now

Or start a personal plan

And upskill your team with Udemy

What's inside

Learning objectives

Maximize your odds of passing the aws certified data engineer - associate (dea-c01) exam
Design and implement data pipelines with aws to ingest, store, and transform data
Choose and design data stores, data models, data schemas, and data lifecycles.
Maintain, operationalize, and orchestrate data pipelines with eventbridge, airflow, aws step functions,, and more

Apply security, governance, and privacy best practices to your aws data pipelines.
Create data lakes with s3, glue, redshift and more
Process batch and streaming data with kinesis, emr, containers, lambda, and more

Maximize your odds of passing the aws certified data engineer - associate (dea-c01) exam
Design and implement data pipelines with aws to ingest, store, and transform data
Choose and design data stores, data models, data schemas, and data lifecycles.
Maintain, operationalize, and orchestrate data pipelines with eventbridge, airflow, aws step functions,, and more
Apply security, governance, and privacy best practices to your aws data pipelines.
Create data lakes with s3, glue, redshift and more
Process batch and streaming data with kinesis, emr, containers, lambda, and more

Syllabus

Introduction

Course Overview - Services we will Cover

Get the Course Materials

Udemy 101

Data Engineering Fundamentals

Intro: Data Engineering Fundamentals

Types of Data (Structured, Unstructured, Semi-Structured)

Properties of Data (Volume / Velocity / Variety)

Data Warehouses vs. Data Lakes (and Lakehouses)

What is a "Data Mesh"?

Managing and Orchestrating ETL Pipelines

Common Data Sources and Data Formats

Quick Review of Data Modeling, Data Lineage, and Schema Evolution

Database Performance Optimization

Data Sampling Techniques

Data Skew Mechanisms

Data Validation and Profiling

SQL Review: Aggregations, Grouping, Sorting, Pivoting

SQL JOIN types

SQL Regular Expressions (a quick intro)

The following three coding exercises allow you to practice solving SQL problems in a hands-on environment!

However, we have heard feedback from some students that Udemy's SQL workspace can be unreliable at times, timing out even on simple queries. If you encounter technical problems, please let Udemy support know. You can visit https://support.udemy.com/hc/en-us/articles/229606768-Learning-With-Coding-Exercises and click on the "Contact Us" button. After some screening from a chatbot, you should be able to file a trouble ticket describing the problem.

Practicing aggregation queries in SQL

Practicing grouping queries in SQL

Practicing join queries in SQL

Git review: architecture and commands

Check your learning from our overview of the data engineering fundamentals called out on the AWS exam guide.

Storage

Intro: Storage

Set up an AWS Billing Alarm

Amazon S3

Amazon S3 - Hands On

Amazon S3 Security - Bucket Policy

Amazon S3 Security - Bucket Policy - Hands On

Amazon S3 - Versioning

Amazon S3 - Versioning - Hands On

Amazon S3 - Replication

Amazon S3 - Replication - Notes

Amazon S3 - Replication - Hands On

Amazon S3 - Storage Classes

Amazon S3 - Storage Classes - Hands On

Amazon S3 - Lifecycle Rules

Amazon S3 - Lifecycle Rules - Hands On

Amazon S3 - Event Notifications

Amazon S3 - Event Notifications - Hands On

Amazon S3 - Performance

Amazon S3 - Select & Glacier Select

Amazon S3 - Encryption

About DSSE-KMS

Amazon S3 - Encryption - Hands On

Amazon S3 - Default Encryption

Amazon S3 - Access Points

Amazon S3 - Object Lambda

Amazon EBS

Amazon EBS - Hands On

Amazon EBS Elastic Volumes

Amazon EFS

Amazon EFS - Hands On

Amazon EFS vs. Amazon EBS

AWS Backup

AWS Backup - Hands On

Test your knowledge of AWS storage services and how they relate to data engineering pipelines.

Database

Intro: Database

Amazon DynamoDB

Amazon DynamoDB - Hands On

Amazon DynamoDB in Big Data

Amazon DynamoDB - Throughput (RCU & WCU)

Amazon DynamoDB - Throughput (RCU & WCU) - Hands On

Amazon DynamoDB - Basic APIs

Amazon DynamoDB - Basic APIs - Hands On

Amazon DynamoDB - Indexes (LSI & GSI)

Amazon DynamoDB - Indexes (LSI & GSI) - Hands On

Amazon DynamoDB - PartiQL

Amazon DynamoDB Accelerator (DAX)

Amazon DynamoDB Accelerator (DAX) - Hands On

Amazon DynamoDB - Streams

Amazon DynamoDB - Streams - Hands On

Amazon DynamoDB - Time To Live (TTL)

Amazon DynamoDB - Patterns with S3

Amazon DynamoDB - Security

Amazon RDS

Shared and exclusive locks in RDS

Amazon RDS Best Practices

Amazon DocumentDB

Amazon MemoryDB for Redis

Amazon Keyspaces (for Apache Cassandra)

Amazon Neptune

Amazon Timestream

Amazon Redshift Intro & Architecture

Redshift Spectrum and Performance Tuning

Redshift Durability and Scaling

Redshift Distribution Styles

Redshift Data Flows and the COPY command

Redshift Integration / WLM / Vacuum

Redshift Resizing

RA3 Nodes, Cross-Region Data Sharing, Redshift ML

Redshift Security

Redshift Serverless

Redshift Materialized Views

Redshift Data Sharing / Data Shares

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers in-demand topics, such as Amazon S3, DynamoDB, and Redshift

Provides guidance for the AWS Certified Data Engineer - Associate Exam, which can be beneficial for career advancement

Offers practical application through hands-on demos and practice questions

Instructors are experienced professionals with industry expertise

Content is up-to-date with the latest developments in AWS data engineering

Course includes lifetime access to future updates, ensuring learners stay current

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AWS Certified Data Engineer Associate 2024 - Hands On! with these activities:

Review SQL Syntax

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Refresh your SQL syntax by completing exercises and reviewing documentation to help you prepare for this course.

Browse courses on SQL

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Review basic SQL syntax, including SELECT, INSERT, UPDATE, and DELETE statements
Practice writing SQL queries to retrieve and manipulate data
Review additional SQL syntax as needed to prepare for the course

Compile a Collection of AWS Data Engineering Tools and Resources

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Strengthen your knowledge base by gathering and organizing a comprehensive list of AWS data engineering tools and resources that you can refer to throughout your learning journey.

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Research and identify AWS data engineering tools
Gather information on each tool, including its purpose, benefits, and use cases
Create a spreadsheet or document to organize the resources

Build a Data Lake with AWS Lake Formation

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Enhance your data lake skills by following a guided tutorial on building and managing a data lake using AWS Lake Formation.

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Set up AWS Lake Formation
Create a data lake
Add data to the data lake
Query data using Athena

Four other activities

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Practice Data Pipeline Design with AWS CLI

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Reinforce your understanding of data pipeline design by practicing with the AWS CLI, which is essential for real-world data engineering tasks.

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Set up your AWS CLI environment
Create an S3 bucket for data storage
Create a DynamoDB table for data storage
Use the AWS CLI to copy data from S3 to DynamoDB
Use the AWS CLI to query data from DynamoDB

Join a Study Group for Data Pipeline Optimization

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Enhance your understanding by collaborating with peers in a study group dedicated to exploring techniques and best practices for optimizing data pipelines.

Browse courses on Data Pipeline Optimization

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Find or create a study group
Establish a regular meeting schedule
Discuss optimization techniques
Share knowledge and experience

Design and Implement a Data Pipeline for a Real-World Dataset

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Apply your knowledge and solidify your understanding by designing and implementing a data pipeline that addresses a real-world business problem.

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Identify a data source
Design the data pipeline
Implement the data pipeline
Evaluate the data pipeline

Mentor Junior Data Engineers on Data Engineering Fundamentals

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Reinforce your own understanding and solidify your knowledge by guiding and assisting junior data engineers in grasping the fundamentals of data engineering.

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