Mastering Amazon Redshift and Serverless for Data Engineers

In-Depth Course on Amazon Redshift, Redshift Serverless, Integration with EMR, AWS Step Functions, AWS Lambda and more

4.47 (195 reviews)

Udemy

platform

English

language

Databases

What you will learn

Getting Started with Amazon Redshift using AWS Web Console

Copy Data from s3 into AWS Redshift Tables using Redshift Queries or Commands

Develop Applications using Redshift Cluster using Python as Programming Language

Copy Data from s3 into AWS Redshift Tables using Python as Programming Language

Create Tables using Databases setup on AWS Redshift Database Server using Distribution Keys and Sort Keys

Run AWS Redshift Federated Queries connecting to traditional RDBMS Databases such as Postgres

Perform ETL using AWS Redshift Federated Queries using Redshift Capacity

Integration of AWS Redshift and AWS Glue Catalog to run queries using Redshift Spectrum

Run AWS Redshift Spectrum Queries using Glue Catalog Tables on Datalake setup using AWS s3

Getting Started with Amazon Redshift Serverless by creating Workgroup and Namespace

Integration of AWS EMR Cluster with Amazon Redshift using Serverless Workgroup

Develop and Deploy Spark Application on AWS EMR Cluster where the processed data will be loaded into Amazon Redshift Serverless Workgroup

Why take this course?

AWS or Amazon Redshift is one of the key AWS Services used in building Data Warehouses or Data Marts to serve reports and dashboards for business users. As part of this course, you will end up learning AWS or Amazon Redshift by going through all the important features of AWS or Amazon Redshift to build Data Warehouses or Data Marts.

We have covered features such as Federated Queries, Redshift Spectrum, Integration with Python, AWS Lambda Functions, Integration of Redshift with EMR, and End-to-End Pipeline using AWS Step Functions.

Here is the detailed outline of the course.

First, we will understand how to Get Started with Amazon Redshift using AWS Web Console. We will see how to create a cluster, how to connect to the cluster, and also how to run the queries using a Web-based query editor. We will also go ahead and create a Database and tables in the Redshift Cluster. Once we set up a Database and tables, we will also go through the details related to CRUD Operations against tables in Databases in Redshift Cluster.
Once we have the databases and tables in Redshift Cluster, it is time for us to understand how to get data into the tables in Redshift Cluster. One of the common approaches we use to get data into the Redshift cluster is by Copying Data from s3 into Redshift Tables. We will go through the step-by-step process of copying the data into Redshift tables from s3 using the copy command.
Python is one of the prominent programming languages to build Data Engineering or ETL Applications. It is extensively used to build ETL Jobs to get data into Database Tables in Redshift Cluster. Once we understand how to get data from s3 to Redshift tables using Copy Command, we will learn how to Develop Python-based Data Engineering or ETL Applications using Redshift Cluster. We will learn how to perform CRUD operations and also how to take run COPY Commands using Python-based programs.
Once we understand how to build applications using Redshift Cluster, we will go through some of the key concepts used while creating Redshift Tables with Distkeys and Sortkeys.
We can also connect to remote databases such as Postgres and run queries directly on the remote database tables using Redshift Federated Queries and also we can run queries on top of Glue or Athena Catalog using Redshift Spectrum. You will learn how to leverage Redshift Federated Queries and Spectrum to process data in remote Database tables or s3 without copying the data.
You will also get an overview of Amazon Redshift Serverless as part of Getting Started with Amazon Redshift Serverless.
Once you learn Amazon Redshift Serverless, you will end up deploying a Pipeline where a Spark Application is deployed on AWS EMR Cluster which will load the data processed by Spark into Redshift.

Reviews

Luis

July 20, 2023

At first I could not find Create Cluster on the first page so I got into Serverless mode. The material is good but talking fast and moving as he is talking make it difficult to follow. Too many times, errors happened and he corrected it, I don't know if it was the way to teach but was annoying. Maybe diagrams of all the things needed before the how it's done could make it better

Gnanaprakasam

May 7, 2023

Strongly recommend this course to get more in depth knowledge on AWS Redshift serverless. It's hands on course and very well explained as usual.

Jeffrey

March 28, 2023

The presentation is robotic. The instructor could be a "text to speech" application with the playback rate set to fast.

Saket

February 3, 2023

Trainer speech is not clear and many times statements are hard to understand and many of the actions/statements repetitive only increasing the length of the course. Some of the concepts are not taught, and took off with running the services. E.g Redshift spectrum architecture wasnt even explained. I bought this course because the content and topics seem to be comprehensive. Disappointed with presentation and losing interest. Still scrolling through the course which might be of interest.

Thimothe

January 5, 2023

Outstanding ! this is one of the best Udemy course. Not only it is project oriented, but build step by step by showing best practices , prototype and production code. Love it.

December 31, 2022

The actual content is very good. However, the audio quality is sometimes unpleasant. Even worse, the narrator speaks very fast, and in some cases, not even the transcript understands what he is saying. If the narrator were to slow down and enunciate the words instead of attempting to get the words out in a hurry without any consideration for the listener, the course would get 5 stars.

Charts

Price

Rating

Enrollment distribution

Mastering Amazon Redshift and Serverless for Data Engineers - Distribution chart