AWS Serverless Analytics: Glue, Redshift, Athena, QuickSight

Created by Siddharth Mehta | Video: 1280×720 | Audio: AAC 48KHz 2ch | Duration: 12:04 H/M | Lec: 119 | 4.80 GB | Language: English

Build Exabyte Scale Serverless Data Lake solution on AWS Cloud with Redshift Spectrum, Glue, Athena, QuickSight, and S3

What you’ll learn
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

Requirements
Basic knowledge of database and data warehouse concepts
Working knowledge of AWS Concepts and Tools like AWS Console, S3, VPC, Security Group, AZ, IAM, Role, Policy etc
Basic working knowledge of any SQL style query language
Working knowledge of Redshift would be an advantage, but is not mandatory. Course covers Redshift cluster development
Course includes demo of all the labs. An AWS Account would be required to try labs hands-on.

Description
PS:

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.

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

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

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

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.

Who this course is for?
Anyone who wants to learn AWS Serverless technologies for data and analytics should take this course
Data Professionals seeking to learn Serverless Storage, Serverless ETL, Serverless Data Analysis and Serverless Reporting should take this course