Mastering AWS Glue, QuickSight, Athena & Redshift Spectrum
- Description
- Curriculum
- FAQ
- Reviews
PS:
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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.
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Course explains all the labs. If you want to practice labs, it would require AWS Account and may cost $$.
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Basic working knowledge of Redshift is recommended, but not a must.
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This course has been designed for intermediate and expert AWS Developers / Architects / Administrators.
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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 !
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11Section Agenda
Section Agenda
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12Amazon Redshift - Introduction and Pre-requisites
Introduction to Amazon Redshift
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13Amazon Redshift - Developing a Redshift Cluster
Develop Amazon Redshift Cluster
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14Amazon Redshift - Installing Client Tools
Install and setup SQL Client to work with Amazon Redshift
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15Amazon Redshift - Installing Sample Data
Load sample data in Redshift cluster
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16Section Agenda
Section Agenda
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17AWS Glue - Architecture
Learn AWS Glue Architecture with diagrams
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18AWS Glue - Terminology
Learn frequently used AWS Glue Terms and their meanings
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19AWS Glue - Applications
Learn about different applications and features of AWS Glue
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20AWS Glue - Internals
Learn internal architecture of AWS Glue
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21AWS Glue - Cost
Learn about the cost economics of AWS Glue
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22Lab: AWS Glue - Security and Privileges Setup
Setup IAM Role and policies to use with AWS Glue
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23AWS Glue - Advance Network Configuration
Learn about the networking concepts and settings required for AWS Glue
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24Lab: AWS Glue - Advance Network Configuration
Configure network settings for AWS Glue
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25Section Agenda
Section Agenda
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26AWS Glue - Data Catalog
Learn about the concept of Data Catalog in AWS Glue
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27Lab: AWS Glue - Databases
Learn to develop databases in AWS Glue
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28AWS Glue - Tables
Learn to develop tables in AWS Glue
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29AWS Glue - Designing Tables
Develop tables manually in AWS Glue
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30Section Agenda
Section Agenda
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31AWS Glue - Introduction to Crawlers
Learn about the concept of Crawler in AWS Glue
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32Lab - Introduction to AWS Glue Classifiers
Learn about the concept of classifiers in AWS Glue
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33Lab 1 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 1
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34Lab 2 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 2
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35Lab 3 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 3
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36Lab 4 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 4
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37Lab 5 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 5
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38Lab 6 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 6
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39Lab 7 - AWS Glue - Developing Data Catalog with Crawlers
Develop crawlers in AWS Glue - Lab 7
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40Section Agenda
Section Agenda
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41Introduction to AWS Glue Jobs
Learn to develop serverless ETL jobs with AWS Glue
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42Lab 1 - Developing AWS Glue Jobs
Learn to develop serverless ETL jobs with AWS Glue
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43AWS Glue Job Properties
Learn about different ETL job properties in AWS Glue
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44Lab 2 - Developing AWS Glue Jobs
Learn to develop serverless ETL jobs with AWS Glue
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45Lab 3 - Assignment : Importing Data from Redshift
Learn to develop serverless ETL jobs with AWS Glue with Redshift as data source
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46Lab 4 - Developing AWS Glue Jobs
Learn to develop serverless ETL jobs with AWS Glue
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47AWS Glue Job Scripts and Properties
Learn to develop Python scripts and properties for serverless ETL jobs using AWS Glue
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48Lab 5 - Developing AWS Glue Jobs
Learn to develop Python scripts and properties for serverless ETL jobs using AWS Glue
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49AWS Glue - Built-in ETL Transformations and Job Bookmarks
Learn about built-in ETL Transformations in AWS Glue
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54Section Agenda
Section Agenda
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55Lab: Creating a AWS Glue Development Endpoint
Learn about AWS Glue Development Endpoints
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56Lab: Installing and configuring Apache Zeppelin
Learn to install and setup Apache Zeppelin
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57Lab: Port Forwarding Configuration
Learn to install Git and setup Port Forwarding
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58Lab: Integrating AWS Glue Development Endpoint with Apache Zeppelin
Learn to integrate AWS Glue Development Endpoint with Apache Zeppelin Notebook
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59AWS Glue Monitoring
Learn monitoring options available for AWS Glue
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6010-Apr-2018 : AWS Glue supports timeout values for ETL Jobs
AWS Glue supports timeout values for ETL Jobs
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6110-Jul-2018 : AWS Glue supports reading from Amazon DynamoDB Tables
AWS Glue supports reading from Amazon DynamoDB Tables
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6213-Jul-2018 : AWS Glue provides additional ETL Job metrics
AWS Glue provides additional ETL Job metrics
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6304-Sep-2018 : AWS Glue supports data encryption at rest
AWS Glue supports data encryption at rest
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6405-Oct-2018 : AWS Glue supports connecting Sagemaker notebooks to dev endpoints
AWS Glue supports connecting Sagemaker notebooks to dev endpoints
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6515-Oct-2018 : AWS Glue supports resource based policies and permissions
AWS Glue supports resource based policies and permissions
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6622-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
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6704-Feb-2019 : Download Source code AWS Glue Data Catalog Client - Hive Metastore
Download Source code AWS Glue Data Catalog Client - Hive Metastore
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6814-Mar-2019 : AWS Glue enables running Apache Spark SQL Queries
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6920-Mar-2019 : AWS Glue supports resource tagging
AWS Glue enables running Apache Spark SQL Queries
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7005-Apr-2019 : AWS Glue supports additional options for memory-intensive jobs
AWS Glue supports additional options for memory-intensive jobs
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7110-May-2019 : AWS Glue crawlers support existing Data Catalog tables as sources
AWS Glue crawlers support existing Data Catalog tables as sources
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7228-May-2019 : AWS Glue enables continuous logging for Spark ETL Jobs
AWS Glue enables continuous logging for Spark ETL Jobs
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7306-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
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7420-Jun-2019 : AWS Glue provides workflows to orchestrate ETL workloads
AWS Glue provides workflows to orchestrate ETL workloads
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7525-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
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7625-Jul-2019 : AWS Glue supports additional options for memory intensive jobs
AWS Glue supports additional options for memory intensive jobs
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7726-Jul-2019 : AWS Glue supports bookmarking Parquet and ORC Files using ETL Jobs
AWS Glue supports bookmarking Parquet and ORC Files using ETL Jobs
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7806-Aug-2019 : Launch AWS Glue, EMR and Aurora Serverless Clusters in Shared VPCs
Launch AWS Glue, EMR and Aurora Serverless Clusters in Shared VPCs
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7909-Aug-2019 : AWS Glue provides FindMatches ML Transform
AWS Glue provides FindMatches ML Transform
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8028-Aug-2019 : AWS Glue releases binaries of Glue ETL libraries for Glue Jobs
AWS Glue releases binaries of Glue ETL libraries for Glue Jobs
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8119-Sep-2019 : AWS Glue provides Apache Spark UI to monitor Glue ETL Jobs
AWS Glue provides Apache Spark UI to monitor Glue ETL Jobs
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8222-Oct-2019 : AWS Glue provides ability to rewind Spark ETL Job bookmarks
AWS Glue provides ability to rewind Spark ETL Job bookmarks
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8322-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
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8425-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
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8516-Jan-2020 : Glue adds new transforms - Purge, Transition and Merge
Glue adds new transforms - Purge, Transition and Merge
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8603-Apr-2020 : Glue supports reading & writing to DocumentDB & MongoDB Collection
Glue supports reading & writing to DocumentDB & MongoDB Collection
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8703-Apr-2020 : AWS Glue supports new tables, update schema & partitions from Jobs
AWS Glue supports new tables, update schema & partitions from Jobs
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8827-Apr-2020 : AWS Glue supports serverless streaming ETL
AWS Glue supports serverless streaming ETL
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