Analyzing your data with Amazon Redshift

DifficultyIntermediate
AVG Duration3h
Students30
Ratings
5/5
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Content
71

Description

Amazon Redshift is a fast, fully-managed, petabyte-scale data warehouse, and designed for high performance and analysis of information capable of storing and processing petabytes of data. Access to this data can be provided using your existing business intelligence tools, using standard SQL. It operates as a relational database management system and therefore is compatible with other RDBMS applications.

In this learning path, you will be introduced to Amazon Redshift and a number of its features to allow you to make use of this service within your production environment.

Intended Audience

This Learning Path is ideal for anyone looking to learn more about the Amazon Redshift, its capabilities, and its features.

Learning Objectives

Following this learning path you will have a better understanding of:

  • The fundamentals of Amazon Redshift 
  • The architecture of Amazon Redshift
  • How to create an Amazon Redshift cluster
  • The essentials of the COPY command in Redshift and its features
  • How to load single or multiple large files into Redshift
  • What upserting is and why it's important
  • The key concepts of data distribution
  • The three types of distribution styles
  • The difference between distribution keys and sort keys
  • The fundamentals of Amazon Redshift concurrency scaling
  • How to set up and activate concurrency scaling
  • Scaling Redshift Clusters
  • How to scale Redshift both horizontally and vertically 
  • The four ways a Redshift Cluster can be scaled
  • Classic resize and elastic resize
  • How to manage cold data in Redshift using Amazon S3
  • What Amazon Redshift Spectrum is and does
  • How Spectrum Queries work
  • Supported data formats of Spectrum
  • File optimization using Spectrum
  • Amazon Redshift Spectrum Considerations


Prerequisites

To get the most from this learning path it would be advantageous to have a basic understanding of data analytic concepts, but it is not essential.

Feedback

If you have any feedback on this learning path then please contact support@cloudacademy.com

Certificate

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Training Content

1
Course - Beginner - 2m
Analyzing your Data with Amazon Redshift
This course introduces the Analyzing your Data with Amazon Redshift learning path.
2
Course - Beginner - 14m
Introduction to Amazon Redshift
Learn about the fastest and most widely used cloud data warehouse provided by AWS, Amazon Redshift.
3
Hands-on Lab - Beginner - 1h 45m
Getting Started with Amazon Redshift
Learn how to use the Amazon Redshift service. Create a cluster with a database, copy data from S3, query data using SQL, and resize the cluster.
4
Course - Intermediate - 23m
Loading Data into Amazon Redshift
This course covers how to load your data efficiently using the COPY command in Amazon Redshift.
5
Course - Intermediate - 16m
Amazon Redshift Distribution Styles
This course explains how Amazon Redshift distributes table data, how keys are used inside tables, and the importance of distribution styles.
6
Course - Intermediate - 11m
Amazon Redshift Concurrency Scaling
This course covers Amazon Redshift's Concurrency Scaling feature, which adds query processing power to a cluster for specific users or queues as needed.
7
Course - Intermediate - 18m
Amazon Redshift Resize Operations
This course covers how to scale Amazon Redshift, focusing on how it can scale storage and compute resources to meet demand.
8
Course - Intermediate - 19m
Amazon Redshift Spectrum
This course covers Amazon Redshift Spectrum, including what it is, what it does, how it works, and some points to take into consideration when using Redshift Spectrum.
About the Author
Students17151
Courses18
Learning paths5

Stephen is the AWS Certification Specialist at Cloud Academy. His content focuses heavily on topics related to certification on Amazon Web Services technologies. He loves teaching and believes that there are no shortcuts to certification but it is possible to find the right path and course of study.

Stephen has worked in IT for over 25 years in roles ranging from tech support to systems engineering. At one point, he taught computer network technology at a community college in Washington state.

Before coming to Cloud Academy, Stephen worked as a trainer and curriculum developer at AWS and brings a wealth of knowledge and experience in cloud technologies.

In his spare time, Stephen enjoys reading, sudoku, gaming, and modern square dancing.