AWS data engineer associate

AWS Certified: Data Engineer – Associate

Course Outline for 8th Grade Audience

Course Objectives:

1. Understand the fundamentals of AWS cloud services and data engineering principles.
2. Learn to design and implement data solutions using AWS services.
3. Develop problem-solving skills through practical AWS data engineering projects.
4. Prepare for the AWS Certified: Data Engineer – Associate certification exam.

Module 1: Introduction to AWS and Cloud Computing

Objective: Understand the basics of cloud computing and AWS.

Learning Outcomes:

• Explain cloud computing and its benefits.
• Identify core AWS services.
• Understand the AWS global infrastructure.

Lessons:

1. What is Cloud Computing?

   • Description: Introduction to cloud computing concepts and benefits.
   • Estimated Time: 30 minutes
   • Challenge Level: Easy
   • Presentation Time: 10 minutes

2. Overview of AWS Services

   • Description: Detailed look at the primary AWS services relevant to data engineering.
   • Estimated Time: 45 minutes
   • Challenge Level: Easy
   • Presentation Time: 15 minutes

3. AWS Global Infrastructure

   • Description: Understanding AWS regions, availability zones, and edge locations.
   • Estimated Time: 30 minutes
   • Challenge Level: Easy
   • Presentation Time: 10 minutes

Module 2: Data Engineering Fundamentals

Objective: Learn basic concepts and tools in data engineering.

Learning Outcomes:

• Understand data storage and processing concepts.
• Identify key data engineering tools and technologies.
• Comprehend ETL (Extract, Transform, Load) processes.

Lessons:

1. Data Storage Basics

   • Description: Introduction to databases, data lakes, and data warehouses.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

2. Data Processing Concepts

   • Description: Understanding batch and stream processing.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

3. ETL Processes

   • Description: Explanation of ETL concepts and tools.
   • Estimated Time: 60 minutes
   • Challenge Level: Moderate
   • Presentation Time: 20 minutes

Module 3: AWS Data Storage Services

Objective: Understand and utilize AWS data storage services.

Learning Outcomes:

• Use Amazon S3, Amazon RDS, and Amazon Redshift.
• Compare and contrast different storage services.
• Understand data security and compliance on AWS.

Lessons:

1. Amazon S3

   • Description: Introduction to Amazon S3, its features, and use cases.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

2. Amazon RDS and Databases

   • Description: Overview of Amazon RDS, its benefits, and supported databases.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

3. Amazon Redshift

   • Description: Introduction to Amazon Redshift for data warehousing.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

Module 4: Data Processing on AWS

Objective: Learn to process data using AWS services.

Learning Outcomes:

• Use AWS Glue for ETL processes.
• Implement data workflows with AWS Lambda.
• Utilize Amazon EMR for big data processing.

Lessons:

1. AWS Glue

   • Description: Detailed look at AWS Glue and its ETL capabilities.
   • Estimated Time: 60 minutes
   • Challenge Level: High
   • Presentation Time: 20 minutes

2. AWS Lambda

   • Description: Introduction to AWS Lambda and serverless data processing.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

3. Amazon EMR

   • Description: Overview of Amazon EMR for big data processing.
   • Estimated Time: 60 minutes
   • Challenge Level: High
   • Presentation Time: 20 minutes

Module 5: Data Security and Compliance

Objective: Understand data security and compliance on AWS.

Learning Outcomes:

• Implement AWS data security best practices.
• Understand compliance requirements for data engineering.
• Use AWS tools for data encryption and monitoring.

Lessons:

1. Data Security Best Practices

   • Description: Overview of data security practices in AWS.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

2. Compliance and Governance

   • Description: Understanding AWS compliance frameworks and governance.
   • Estimated Time: 45 minutes
   • Challenge Level: Moderate
   • Presentation Time: 15 minutes

3. Encryption and Monitoring Tools

   • Description: Using AWS tools for data encryption and monitoring.
   • Estimated Time: 60 minutes
   • Challenge Level: High
   • Presentation Time: 20 minutes

Module 6: Practical Projects and Exam Preparation

Objective: Apply knowledge through practical projects and prepare for certification.

Learning Outcomes:

• Complete practical AWS data engineering projects.
• Review key concepts for the certification exam.
• Develop exam-taking strategies.

Lessons:

1. Practical Project 1: Data Lake Implementation

   • Description: Build and manage a data lake using AWS services.
   • Estimated Time: 120 minutes
   • Challenge Level: High
   • Presentation Time: 30 minutes

2. Practical Project 2: Real-time Data Processing

   • Description: Implement a real-time data processing pipeline.
   • Estimated Time: 120 minutes
   • Challenge Level: High
   • Presentation Time: 30 minutes

3. Certification Exam Preparation

   • Description: Review key topics and practice exam questions.
   • Estimated Time: 90 minutes
   • Challenge Level: High
   • Presentation Time: 30 minutes

Total Course Duration

• Estimated Learning Time: 20 hours
• Presentation Time: 7 hours

Potential Challenges:

• Grasping complex data engineering concepts at a young age.
• Managing the practical application of AWS services.
• Retaining extensive AWS service knowledge for certification preparation.

https://d1.awsstatic.com/training-and-certification/docs-data-engineer-associate/AWS-Certified-Data-Engineer-Associate_Exam-Guide.pdf

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 hands-on exercises and 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 explanations. Then, determine your readiness to take the exam with the Official Pretest.

Course level: Fundamental

Duration: 13 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 (Question Set, Bonus Questions, and Official Pretest) 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:

1. Understand the knowledge tested by the AWS Certified Data Engineer - Associate (DEA-C01) exam.
2. Evaluate your gaps in knowledge of the exam topics.
3. Validate your readiness to take the exam.

Intended audience

This course is intended for individuals who meet all of the following requirements:

1. Have the equivalent of 2–3 years of experience in data engineering.
2. Have 1–2 years of hands-on experience with AWS services.
3. 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:

• AWS Cloud Practitioner Essentials
• Fundamentals of Analytics on AWS – Part 1
• Fundamentals of Analytics on AWS – Part 2
• Getting Started with AWS Storage
• Planning Large Scale Data Migration to AWS
• Digital Classroom - Cloud Operations on AWS 

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

Get to know AWS services and best practices by exploring AWS whitepapers, FAQs, and documentation relevant to your exam:

• Data Lakes and Analytics on AWS
• Architecture Best Practices for Analytics & Big Data
• Big Data Analytics Options on AWS 
• Data Residency: AWS Policy Perspectives
• Data Analytics LensYou also can enroll in these instructor-led trainings:

• Building Batch Data Analytics  Solutions on AWS  
• Building Data Lakes on AWS

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 Question Set (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
• Lab Assessment 1: Ingesting and Transforming Data by Using Amazon EMR and Apache Spark
• AWS Certified Data Engineer - Associate Bonus Questions (DEA-C01 - English) - Domain 1
• Additional resources
• Flashcards

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
• Lab Assessment 2: Data Store Management that Uses DynamoDB and AWS Glue
• AWS Certified Data Engineer - Associate Bonus Questions (DEA-C01 - English) - Domain 2
• Additional resources
• Flashcards

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
• Lab Assessment 3: Analyzing Data by Using Athena
• AWS Certified Data Engineer - Associate Bonus Questions (DEA-C01 - English) - Domain 3
• Additional resources
• Flashcards

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
• Lab Assessment 4: Managing Data Access in Amazon S3 by Using VPC Endpoints and S3 Access Points
• AWS Certified Data Engineer - Associate Bonus Questions (DEA-C01 - English) - Domain 4
• Additional resources
• Flashcards

Module 5: Determine exam readiness

• Introduction to Official Pretests
• Overview and Instructions: Official Pretest
• AWS Certified Data Engineer - Associate Official Pretest (DEA-C01 - English)

Module 6: Register for the exam

Module 7: Course close

Module 8: Course survey