Course Details!


In late 2019, AWS announced they would be renaming the AWS Big Data Specialty certification to the AWS Data Analytics – Specialty certification. There are some carryover topics with these changes, but many of the topics are brand new and more in-depth. This course is designed to teach you the new services and tools you can use in AWS to build data analytics applications, as well as build and manage the lifecycle of collecting, storing, processing, and visualizing your data.
This credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives. Earning AWS Certified Data Analytics – Specialty validates expertise in using AWS data lakes and analytics services to get insights from data.
Who should take this course?
AWS Certified Data Analytics – Specialty is intended for individuals with experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions. Before you take this exam, we recommend you have: Five years of experience with common data analytics technologies
Two years of hands-on experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions
Ability to define AWS data analytics services and understand how they integrate with each other
Ability to explain how AWS data analytics services fit in the data lifecycle of collection, storage, processing, and visualization

What Will I Learn?

  • In this course, we cover major tools, topics, and services needed for a successful data analytics pipeline to help you gain hands-on experience and pass the exam.


  • Data Analytics – Specialty

Chapter 1 (Introduction)

  • Welcome to the Course!
  • Prerequisites and Course Overview
  • Exam Overview
  • What is Data Analytics?

Chapter 2 (Amazon Simple Storage Service)

  • Introduction to S3
  • Getting Data Into S3 - Concepts, AWS Management Console, AWS CLI (Part 1)
  • Getting Data Into S3 - Boto3 (Part 2)
  • S3 Multipart Upload (Part 1)
  • S3 Multipart Upload (Part 2)
  • S3 Storage Classes
  • S3 Lifecycle Policies
  • S3 Security and Encryption
  • Checkpoint
  • Programmatically Utilizing Data From S3

Chapter 3 (Databases In AWS)

  • Introduction to Databases in AWS
  • Database Engine Types
  • Relational Database Service (RDS)
  • Neptune
  • DocumentDB
  • Serverless Options
  • Checkpoint
  • Programmatically Utilizing S3 Select

Chapter 4 (Collecting Streaming Data)

  • Introduction to Collecting Streaming Data
  • The Kinesis Family
  • Kinesis Data Streams (Part 1)
  • Kinesis Data Streams (Part 2)
  • Kinesis Data Firehose (Part 1)
  • Kinesis Data Firehose (Part 2)
  • Kinesis Video Streams
  • Kinesis Data Analytics (Part 1)
  • Kinesis Data Analytics (Part 2)
  • Amazon Managed Service for Kafka (MSK)
  • Checkpoint
  • Joining, Enriching, and Transforming Streaming Data with Amazon Kinesis

Chapter 6 (Amazon Elastic Map Reduce (EMR))

  • Introduction to Amazon Elastic Map Reduce (EMR)
  • Apache Hadoop and EMR Software Collection
  • EMR Architecture
  • EMR Operations - Transient vs Long-Running
  • EMR Operations - Choosing an Instance Type
  • EMR Operations - Choosing the Right Number of Instances
  • EMR Operations - On-Demand and Spot Instances
  • EMR Operations - Monitoring and Resizing Clusters
  • EMR File Storage and Compression
  • Checkpoint
  • Data Analytics with Spark and EMR

Chapter 7 (Using Redshift)

  • Introduction to Using Redshift
  • Redshift Architecture
  • Redshift in the AWS Service Ecosystem
  • Redshift Use Cases
  • Redshift Table Design
  • Redshift Spectrum
  • Querying Data from Multiple Redshift Spectrum Tables

Chapter 8 (Redshift Maintenance and Operations)

  • Launching a Redshift Cluster
  • Resizing a Redshift Cluster
  • Utilizing Vacuum and Deep Copy
  • Backup and Restore
  • Monitoring
  • Checkpoint
  • Manually Migrating Data Between Redshift Clusters

Chapter 9 (AWS Glue, Athena, and QuickSight)

  • Introduction to AWS Glue, Athena, and QuickSight
  • Glue Data Catalog (Part 1)
  • Glue Data Catalog (Part 2)
  • Glue Jobs (Part 1)
  • Glue Job Demo (Part 2)
  • Glue Jobs (Part 3)
  • 12:07
  • Job Bookmarks
  • Getting Started with Athena
  • Athena Demo
  • When To Use Athena
  • QuickSight Visualizations and Dashboards
  • QuickSight Security and Authentication
  • Checkpoint

Chapter 10 (Elasticsearch)

  • Introduction to Elasticsearch
  • Using Elasticsearch
  • Visualizing Elasticsearch Data
  • Checkpoint
  • Implementing an Elasticsearch Backed Search Microservice

Chapter 11 (AWS Security Services)

  • Introduction to AWS Security Services
  • IAM
  • KMS
  • Secrets Manager
  • VPC Network Security Features
  • Checkpoint
  • Advanced S3 Security Configuration

Chapter 12 (Wrap-Up)

  • Congratulations
  • AWS Data Analytics Specialty - Practice Exam