Hands-On Amazon Redshift for Data Warehousing

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.

About The Author

Colibri Digital is a technology consultancy company founded in 2015 by James and Ingrid Cross. 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 tier 1 investment banks, a leading management consultancy group, and one of the world’s most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways.

At the frontier of AI, big data and cloud computing, we are Colibri Digital.

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 a 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 the CTO of Scout Solutions Ltd, he built a fully serverless set of API’s and an analytics stack based around Lambda and Redshift.

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Frequently Asked Questions

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