Amazon Redshift is a low-cost cloud data platform that can scale from gigabytes to petabytes on a high-performance, column-oriented SQL engine. Amazon Redshift brings the power of scale-out architecture to the world of traditional data warehousing.
In this course, you will explore this low-cost, cloud-based storage, which can be scaled up or down to meet your true size and performance needs. You will learn to configure a sample data warehouse. Next, you will explore Redshift's internal workings and architecture, and learn what makes it so fast. You will get hands-on experience connecting, querying, and building BI and data viz products and learn how to secure, maintain, and administer your new platform.
By the end of this course, you will be able to scale from gigabytes to petabytes on this high-performance, column-oriented SQL engine.
What You Will Learn
- Understand data warehousing principles and how Redshift is challenging the traditional way of thinking
- See how Redshift integrates with the AWS Cloud ecosystem
- Learn how Redshift leverages the latest technology to provide up to 10x the performance of competing technologies
- Create a cloud-native, fully managed data warehouse and use it to join together disparate data sets
- Connect your new data warehouse with disjointed data stored on Amazon S3 with Redshift Spectrum
- Visualize your newly connected data sets with Amazon QuickSight
- Dive headfirst into building a Redshift data warehouse using a diversified data set
- Connect to and optimize your data warehouse and join data sets together
- Connect data in your data warehouse with data on Amazon S3 with Redshift Spectrum
If you are a data analyst, data scientist, or AWS professional and are looking for a data warehouse solution using AWS services, then this course is for you! It is also suitable for professionals using DynamoDB, RDS, or any other AWS Database services. Familiarity with AWS is assumed.
About The Author
Colibri Digital: Colibri is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas like big data, data science, machine learning, and cloud computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the world's most popular soft drinks companies, helping each of them to make better sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.
James Cross is a Big Data Engineer and certified AWS Solutions Architect with a passion for data-driven applications. He's spent the last 3-5 years helping his clients to design and implement huge-scale, streaming big data platforms, cloud-based analytics stacks, and serverless architectures.
He started his professional career in Investment Banking, working with well-established technologies such as Java and SQL Server, before moving into the Big Data space. Since then he's worked with a huge range of big data tools including most of the Hadoop eco-system, Spark, and many No-SQL technologies such as Cassandra, MongoDB, Redis, and DynamoDB. More recently his focus has been on cloud technologies and how they can be applied to data analytics, culminating in his work at Scout Solutions as CTO, and more recently with Mckinsey.
James is an AWS certified solutions architect with several years' experience designing and implementing solutions on this cloud platform. As CTO of Scout Solutions Ltd, he built a fully serverless set of APIs and an analytics stack based around Lambda and Redshift.
Table of contents
- Chapter 1 : Data Warehousing for the Internet Age
- Chapter 2 : Getting Started with Redshift
- Chapter 3 : Creating a Redshift Data Warehouse from Disparate Datasets
- Chapter 4 : Optimizing Redshift for Scale
- Chapter 5 : Connecting Redshift with Disconnected Data Using Redshift Spectrum
- Chapter 6 : Visualizing Your Results with Amazon QuickSight
- Title: Hands-On Amazon Redshift for Data Warehousing
- Release date: January 2019
- Publisher(s): Packt Publishing
- ISBN: 9781838558888
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