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Mastering AWS Glue, QuickSight, Athena & Redshift Spectrum

Master serverless analytics with AWS Glue, QuickSight, Athena, & Redshift Spectrum (includes preview features with labs)
Instructor:
Siddharth Mehta
7,430 students enrolled
Confidently work with AWS Serverless services to develop Data Catalogue, ETL, Analytics and Reporting on a Data Lake
Develop deep knowledge in Glue, Athena, Redshift Spectrum and QuickSight
Build a serverless data lake on AWS using structured and unstructured data
Architect Serverless Analytics solutions on AWS cloud platform

PS:

  1. Please do NOT join the course if you do NOT have any basic working knowledge of AWS Console and AWS Services like S3, IAM, VPC, Security Groups etc. AWS Beginners may struggle understanding some of the topics.

  2. Course explains all the labs. If you want to practice labs, it would require AWS Account and may cost $$.

  3. Basic working knowledge of Redshift is recommended, but not a must.

  4. This course has been designed for intermediate and expert AWS Developers / Architects / Administrators.

  5. Course covers each and every feature that AWS has released since 2018 for AWS Glue, AWS QuickSight, AWS Athena, and Amazon Redshift Spectrum, and it regularly updated with every new feature released for these services.

Serverless is the future of cloud computing and AWS is continuously launching new services on Serverless paradigm. AWS launched Athena and QuickSight in Nov 2016, Redshift Spectrum in Apr 2017, and Glue in Aug 2017. Data and Analytics on AWS platform is evolving and gradually transforming to serverless mode.

Businesses have always wanted to manage less infrastructure and more solutions. Big data challenges are continuously challenging the infrastructure boundaries. Having Serverless Storage, Serverless ETL, Serverless Analytics, and Serverless Reporting, all on one cloud platform had sounded too good to be true for a very long time. But now its a reality on AWS platform. AWS is the only cloud provider that has all the native serverless components for a true Serverless Data Lake Analytics solution.

It’s not a secret that when a technology is new in the industry, professionals with expertise in new technologies command great salaries. Serverless is the future, Serverless is the industry demand, and Serverless is new. It’s the perfect time and opportunity to jump into Serverless Analytics on AWS Platform.

In this course, we would learn the following:

1) We will start with Basics on Serverless Computing and Basics of Data Lake Architecture on AWS.

2) We will learn Schema Discovery, ETL, Scheduling, and Tools integration using Serverless AWS Glue Engine built on Spark environment.

3) We will learn to develop a centralized Data Catalogue too using Serverless AWS Glue Engine.

4) We will learn to query data lake using Serverless Athena Engine build on the top of Presto and Hive.

5) We will learn to bridge the data warehouse and data lake using Serverless Amazon Redshift Spectrum Engine built on the top of Amazon Redshift platform.

6) We will learn to develop reports and dashboards, with a powerpoint like slideshow feature, and mobile support, without building any report server, by using Serverless Amazon QuickSight Reporting Engines.

7) We will finally learn how to source data from data warehouse, data lake, join data, apply row security, drill-down, drill-through and other data functions using the Serverless Amazon QuickSight Reporting Engines.

This course understands your time is important, and so the course is designed to be laser-sharp on lecture timings, where all the trivial details are kept at a minimum and focus is kept on core content for experienced AWS Developers / Architects / Administrators. By the end of this course, you can feel assured and confident that you are future-proof for the next change and disruption sweeping the cloud industry.

I am very passionate about AWS Serverless computing on Data and Analytics platform, and am covering A-to-Z of all the topics discussed in this course.

So if you are excited and ready to get trained on AWS Serverless Analytics platform, I am ready to welcome you in my class !

Introduction

1
Instructor and Course Introduction

Instructor and Course Introduction

2
Pre-requisites - What you'll need for this course

Pre-requisites - What you'll need for this course

3
Course Objectives

Course Objectives

4
Course Content, Convention and Resources

Course Content, Convention and Resources

AWS Serverless Analytics and Data Lake Basics

1
Section Agenda

Section Agenda

2
What is Serverless Computing ?

Learn about basics of Serverless Computing and which AWS Services fits into it

3
Basics of AWS Serverless Data Lake Architecture

Learn basics of AWS Serverless Data Lake Architecture

Amazon S3 - Test-Data Setup

1
Section Agenda

Section Agenda

2
Lab: Sample Data Setup on Amazon S3

Setup sample data on S3 buckets that would be used throughout this course

3
Lab: Amazon S3 - Analytics Configuration

Configure S3 Storage Analytics

Amazon Redshift - Cluster and Sample Data Setup

1
Section Agenda

Section Agenda

2
Amazon Redshift - Introduction and Pre-requisites

Introduction to Amazon Redshift

3
Amazon Redshift - Developing a Redshift Cluster

Develop Amazon Redshift Cluster

4
Amazon Redshift - Installing Client Tools

Install and setup SQL Client to work with Amazon Redshift

5
Amazon Redshift - Installing Sample Data

Load sample data in Redshift cluster

AWS Glue - Architecture and Setup

1
Section Agenda

Section Agenda

2
AWS Glue - Architecture

Learn AWS Glue Architecture with diagrams

3
AWS Glue - Terminology

Learn frequently used AWS Glue Terms and their meanings

4
AWS Glue - Applications

Learn about different applications and features of AWS Glue

5
AWS Glue - Internals

Learn internal architecture of AWS Glue

6
AWS Glue - Cost

Learn about the cost economics of AWS Glue

7
Lab: AWS Glue - Security and Privileges Setup

Setup IAM Role and policies to use with AWS Glue

8
AWS Glue - Advance Network Configuration

Learn about the networking concepts and settings required for AWS Glue

9
Lab: AWS Glue - Advance Network Configuration

Configure network settings for AWS Glue

AWS Glue - Database Objects

1
Section Agenda

Section Agenda

2
AWS Glue - Data Catalog

Learn about the concept of Data Catalog in AWS Glue

3
Lab: AWS Glue - Databases

Learn to develop databases in AWS Glue

4
AWS Glue - Tables

Learn to develop tables in AWS Glue

5
AWS Glue - Designing Tables

Develop tables manually in AWS Glue

AWS Glue - Crawlers

1
Section Agenda

Section Agenda

2
AWS Glue - Introduction to Crawlers

Learn about the concept of Crawler in AWS Glue

3
Lab - Introduction to AWS Glue Classifiers

Learn about the concept of classifiers in AWS Glue

4
Lab 1 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 1

5
Lab 2 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 2

6
Lab 3 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 3

7
Lab 4 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 4

8
Lab 5 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 5

9
Lab 6 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 6

10
Lab 7 - AWS Glue - Developing Data Catalog with Crawlers

Develop crawlers in AWS Glue - Lab 7

AWS Glue - ETL Jobs

1
Section Agenda

Section Agenda

2
Introduction to AWS Glue Jobs

Learn to develop serverless ETL jobs with AWS Glue

3
Lab 1 - Developing AWS Glue Jobs

Learn to develop serverless ETL jobs with AWS Glue

4
AWS Glue Job Properties

Learn about different ETL job properties in AWS Glue

5
Lab 2 - Developing AWS Glue Jobs

Learn to develop serverless ETL jobs with AWS Glue

6
Lab 3 - Assignment : Importing Data from Redshift

Learn to develop serverless ETL jobs with AWS Glue with Redshift as data source

7
Lab 4 - Developing AWS Glue Jobs

Learn to develop serverless ETL jobs with AWS Glue

8
AWS Glue Job Scripts and Properties

Learn to develop Python scripts and properties for serverless ETL jobs using AWS Glue

9
Lab 5 - Developing AWS Glue Jobs

Learn to develop Python scripts and properties for serverless ETL jobs using AWS Glue

10
AWS Glue - Built-in ETL Transformations and Job Bookmarks

Learn about built-in ETL Transformations in AWS Glue

AWS Glue - Triggers

1
Section Agenda

Section Agenda

2
Introduction to AWS Glue Triggers

Learn about Triggers in AWS Glue

3
Lab 1 - Developing AWS Glue Triggers

Learn about Triggers in AWS Glue

4
Lab 2 - Developing AWS Glue Triggers

Learn about Triggers in AWS Glue

AWS Glue - Dev Ops Setup

1
Section Agenda

Section Agenda

2
Lab: Creating a AWS Glue Development Endpoint

Learn about AWS Glue Development Endpoints

3
Lab: Installing and configuring Apache Zeppelin

Learn to install and setup Apache Zeppelin

4
Lab: Port Forwarding Configuration

Learn to install Git and setup Port Forwarding

5
Lab: Integrating AWS Glue Development Endpoint with Apache Zeppelin

Learn to integrate AWS Glue Development Endpoint with Apache Zeppelin Notebook

6
AWS Glue Monitoring

Learn monitoring options available for AWS Glue

AWS Glue New Features and Releases : 2018, 2019, 2020

1
10-Apr-2018 : AWS Glue supports timeout values for ETL Jobs

AWS Glue supports timeout values for ETL Jobs

2
10-Jul-2018 : AWS Glue supports reading from Amazon DynamoDB Tables

AWS Glue supports reading from Amazon DynamoDB Tables

3
13-Jul-2018 : AWS Glue provides additional ETL Job metrics

AWS Glue provides additional ETL Job metrics

4
04-Sep-2018 : AWS Glue supports data encryption at rest

AWS Glue supports data encryption at rest

5
05-Oct-2018 : AWS Glue supports connecting Sagemaker notebooks to dev endpoints

AWS Glue supports connecting Sagemaker notebooks to dev endpoints

6
15-Oct-2018 : AWS Glue supports resource based policies and permissions

AWS Glue supports resource based policies and permissions

7
22-Jan-2019 : AWS Glue introduces Python Shell Jobs

AWS Glue introduces Python Shell Jobs which can be used for custom transformations and other generic tasks in ETL jobs

8
04-Feb-2019 : Download Source code AWS Glue Data Catalog Client - Hive Metastore

Download Source code AWS Glue Data Catalog Client - Hive Metastore

9
14-Mar-2019 : AWS Glue enables running Apache Spark SQL Queries
10
20-Mar-2019 : AWS Glue supports resource tagging

AWS Glue enables running Apache Spark SQL Queries

11
05-Apr-2019 : AWS Glue supports additional options for memory-intensive jobs

AWS Glue supports additional options for memory-intensive jobs

12
10-May-2019 : AWS Glue crawlers support existing Data Catalog tables as sources

AWS Glue crawlers support existing Data Catalog tables as sources

13
28-May-2019 : AWS Glue enables continuous logging for Spark ETL Jobs

AWS Glue enables continuous logging for Spark ETL Jobs

14
06-Jun-2019 : AWS Glue supports scripts compatible with Python 3.6 in Shell Jobs

AWS Glue supports scripts compatible with Python 3.6 in Shell Jobs

15
20-Jun-2019 : AWS Glue provides workflows to orchestrate ETL workloads

AWS Glue provides workflows to orchestrate ETL workloads

16
25-Jul-2019 : AWS Glue supports running ETL Jobs on Spark 2.4.3 with Python 3

AWS Glue supports running ETL Jobs on Spark 2.4.3 with Python 3

17
25-Jul-2019 : AWS Glue supports additional options for memory intensive jobs

AWS Glue supports additional options for memory intensive jobs

18
26-Jul-2019 : AWS Glue supports bookmarking Parquet and ORC Files using ETL Jobs

AWS Glue supports bookmarking Parquet and ORC Files using ETL Jobs

19
06-Aug-2019 : Launch AWS Glue, EMR and Aurora Serverless Clusters in Shared VPCs

Launch AWS Glue, EMR and Aurora Serverless Clusters in Shared VPCs

20
09-Aug-2019 : AWS Glue provides FindMatches ML Transform

AWS Glue provides FindMatches ML Transform

21
28-Aug-2019 : AWS Glue releases binaries of Glue ETL libraries for Glue Jobs

AWS Glue releases binaries of Glue ETL libraries for Glue Jobs

22
19-Sep-2019 : AWS Glue provides Apache Spark UI to monitor Glue ETL Jobs

AWS Glue provides Apache Spark UI to monitor Glue ETL Jobs

23
22-Oct-2019 : AWS Glue provides ability to rewind Spark ETL Job bookmarks

AWS Glue provides ability to rewind Spark ETL Job bookmarks

24
22-Nov-2019 :AWS Glue support FindMatches ML Transform on Spark 2.4.3 & Glue 1.0

AWS Glue support FindMatches ML Transform on Spark 2.4.3 & Glue 1.0

25
25-Nov-2019 : AWS Glue supports bringing your own JDBC driver for Spark ETL Jobs

AWS Glue supports bringing your own JDBC driver for Spark ETL Jobs

26
16-Jan-2020 : Glue adds new transforms - Purge, Transition and Merge

Glue adds new transforms - Purge, Transition and Merge

27
03-Apr-2020 : Glue supports reading & writing to DocumentDB & MongoDB Collection

Glue supports reading & writing to DocumentDB & MongoDB Collection

28
03-Apr-2020 : AWS Glue supports new tables, update schema & partitions from Jobs

AWS Glue supports new tables, update schema & partitions from Jobs

29
27-Apr-2020 : AWS Glue supports serverless streaming ETL

AWS Glue supports serverless streaming ETL

AWS Athena - Architecture and Setup

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