Summary

In this chapter, we reviewed how data is becoming ever more important for organizations looking to gain new insights and competitive advantage, and introduced some of the core big data processing technologies. We also looked at the key roles related to managing, processing, and analyzing large datasets, and highlighted how cloud technologies enable organizations to better deal with the increasing volume, variety, and velocity of data.

In our first hands-on exercise, we provided step-by-step instructions for creating a new AWS account that can be used throughout the remainder of this book as we develop our own data engineering pipeline.

In the next chapter, we dig deeper into current approaches, tools, and frameworks that are commonly used to manage and analyze large datasets, including data warehouses, data marts, data lakes, and a relatively new concept, the data lake house. We also get hands-on with AWS again, this time installing and configuring the AWS Command-Line Interface (CLI) tool and creating an Amazon S3 bucket.