AWS Certified Data Analytics - Specialty

By John Hanna
By Brock Tubre

This course is for software developers and data professionals who want to learn about data analytics on the AWS platform.

10 hours
  • 85 Lessons
  • 1 Practice Exam

About the course

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.

Just because the name of the certification is changing doesn’t mean big data is going away. In fact, data is growing for organizations at an alarming rate, and that means there is a growing need for engineers who know how to gather insight from that data. That is where the AWS Data Analytics Specialty certification fits into the picture. This certification validates a deep understanding of AWS data analytics services and how they integrate with each other. Once you have passed the exam, you should be able to explain how AWS data analytics services fit into the data lifecycle and answer important questions about what your organization’s data is providing.

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. So when you’re ready, join us in the AWS Data Analytics – Specialty course!

  • Chapter 1 4 Lessons Introduction 24:33

    Welcome to the Course!

    3:53

    Prerequisites and Course Overview

    9:12

    Exam Overview

    6:48

    What is Data Analytics?

    4:40
  • Chapter 2 9 Lessons Amazon Simple Storage Service 1:43:55

    Introduction to S3

    1:27

    Getting Data Into S3 - Concepts, AWS Management Console, AWS CLI (Part 1)

    15:37

    Getting Data Into S3 - Boto3 (Part 2)

    11:56

    S3 Multipart Upload (Part 1)

    10:48

    S3 Multipart Upload (Part 2)

    13:03

    S3 Storage Classes

    14:13

    S3 Lifecycle Policies

    10:17

    S3 Security and Encryption

    17:53

    Checkpoint

    8:41
  • Chapter 3 7 Lessons Databases In AWS 50:03

    Introduction to Databases In AWS

    1:54

    Database Engine Types

    8:49

    Relational Database Service (RDS)

    7:52

    Neptune

    6:15

    DocumentDB

    3:26

    Serverless Options

    13:00

    Checkpoint

    8:47
  • Chapter 4 11 Lessons Collecting Streaming Data 1:42:49

    Introduction to Collecting Streaming Data

    1:18

    The Kinesis Family

    5:25

    Kinesis Data Streams (Part 1)

    9:23

    Kinesis Data Streams (Part 2)

    14:34

    Kinesis Data Firehose (Part 1)

    6:36

    Kinesis Data Firehose (Part 2)

    13:49

    Kinesis Video Streams

    8:12

    Kinesis Data Analytics (Part 1)

    6:54

    Kinesis Data Analytics (Part 2)

    12:45

    Amazon Managed Service for Kafka (MSK)

    12:13

    Checkpoint

    11:40
  • Chapter 5 8 Lessons Data Collection and Getting Data Into AWS 1:11:46

    Introduction to Data Collection and Getting Data Into AWS

    1:23

    Direct Connect, Snowball, Snowball Edge, Snowmobile

    13:51

    Database Migration Service

    9:35

    Data Pipeline

    8:40

    Lambda, API Gateway, and CloudFront (Part 1)

    7:21

    Lambda, API Gateway, and CloudFront (Part 2)

    11:15

    Comparing Our Options

    7:25

    Checkpoint

    12:16
  • Chapter 6 10 Lessons Amazon Elastic Map Reduce (EMR) 1:21:03

    Introduction to Amazon Elastic Map Reduce (EMR)

    1:15

    Apache Hadoop and EMR Software Collection

    12:06

    EMR Architecture

    10:48

    EMR Operations - Transient vs Long-Running

    7:46

    EMR Operations - Choosing an Instance Type

    3:05

    EMR Operations - Choosing the Right Number of Instances

    8:58

    EMR Operations - On-Demand and Spot Instances

    5:15

    EMR Operations - Monitoring and Resizing Clusters

    12:58

    EMR File Storage and Compression

    10:03

    Checkpoint

    8:49
  • Chapter 7 6 Lessons Using Redshift 51:47

    Introduction to Using Redshift

    2:15

    Redshift Architecture

    6:37

    Redshift in the AWS Service Ecosystem

    6:43

    Redshift Use Cases

    5:27

    Redshift Table Design

    13:33

    Redshift Spectrum

    17:12
  • Chapter 8 6 Lessons Redshift Maintenance and Operations 1:07:11

    Launching a Redshift Cluster

    13:52

    Resizing a Redshift Cluster

    11:47

    Utilizing Vacuum and Deep Copy

    12:05

    Backup and Restore

    7:42

    Monitoring

    10:53

    Checkpoint

    10:52
  • Chapter 9 13 Lessons AWS Glue, Athena, and QuickSight 2:06:27

    Introduction to AWS Glue, Athena, and QuickSight

    1:41

    Glue Data Catalog (Part 1)

    9:36

    Glue Data Catalog (Part 2)

    10:33

    Glue Jobs (Part 1)

    4:40

    Glue Job Demo (Part 2)

    11:39

    Glue Jobs (Part 3)

    12:07

    Job Bookmarks

    8:33

    Getting Started with Athena

    9:55

    Athena Demo

    11:31

    When To Use Athena

    7:43

    QuickSight Visualizations and Dashboards

    11:00

    QuickSight Security and Authentication

    12:01

    Checkpoint

    15:28
  • Chapter 10 4 Lessons Elasticsearch 34:06

    Introduction to Elasticsearch

    3:13

    Using Elasticsearch

    15:05

    Visualizing Elasticsearch Data

    7:52

    Checkpoint

    7:56
  • Chapter 11 6 Lessons AWS Security Services 30:31

    Introduction to AWS Security Services

    3:02

    IAM

    6:05

    KMS

    4:49

    Secrets Manager

    4:03

    VPC Network Security Features

    7:17

    Checkpoint

    5:15
  • Chapter 12 2 Lessons Wrap-Up 3:01:24

    Congratulations

    1:24

    AWS Data Analytics Specialty - Practice Exam

    3:00:00 Quiz

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