A Real World Introduction to Amazon's Redshift

A Real World Introduction to Amazon's Redshift

Note: The vast majority of the first section is free. Please view these free videos. They will give you an idea of how the rest of the course is structured. Thank you. 

Although a gross oversimplification, Amazon Redshift is a traditional data warehouse platform.

Data warehousing has been around for quite a number of years now. There have been many evolutions in data modeling, storage, and ultimately the vast variety of tools that the business user now has available to help utilize their quickly growing stores of data.

As the industry is moving more towards self service business intelligence solutions for business users, there are also changes in how data is being stored. Amazon Redshift is one of those "game-changing" platforms that is not only driving down the total cost, but also driving up the ability to store even more data to enable even better business decisions to be made.

One of the greatest features about all Amazon’s service is that much of the mundane administration tasks have been removed. The hardware, software patching, and disk management (all of which are no small tasks) have been taken on by Amazon. Disk management, particularly the automated recovery from disk failure, and even the ability to begin querying a cluster that is being restored (even before it is done) are all powerful and compelling things Amazon has done to reduce your workload and increase up-time.

In the course we will create nodes, called redshift cluster. Once we spun up a node we can upload our data sets and perform data analysis. We will walk through all the steps necessary to begin using a redshift cluster in the real world.

One of the greatest benefits of Redshift is blazing fast query performance. There are two core items that are responsible for this. The use of columnar storage technology to improve I/O efficiency and parallelizing queries across multiple nodes. The parallelizing of queries across many nodes is known as MPP or Massive Parallel Processing.

The underlying hardware is designed for high performance data processing, using local attached storage to maximize throughput between the CPUs and drives, and a 10GigE mesh network to maximize throughput between nodes.

The last nail in the coffin for the traditional brick and mortal data warehouse is cost. Redshift accomplishes all this at a fraction of the cost of the traditional data warehouse.

If you are looking to expand your knowledge about Amazon’s data platform and specially about their Redshift service then this course is for you.

Thank you and welcome to Redshift.

Learn how to spin up Redshift Clusters and load data into Redshift Tables

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What you will learn

• Be able to provision a Redshift Data Warehouse Cluster
• You'll learn how to create tables and load data
• The course was designed for DBAs and developers who want to get up to speed with Redshift as quickly as possible.

Rating: 3.95

Level: Intermediate Level

Duration: 1 hour

Instructor: Mike West