Ingesting, processing, normalizing, extracting, transforming, and loading are all activities we do with raw data. Each of our organizations has a wealth of raw data of different types and classifications. To be able to make sense and draw greater meaning from this data, we need to be able to store, process, and identify patterns on a huge scale. The services provided by AWS make it easier for us to process data by taking away the undifferentiated heavy lifting of building and operating enterprise-scale data management solutions.

The focus of this chapter is to give you an introduction to how to process data using serverless services in AWS. As you can imagine, it would be impossible to cover all the aspects of data processing in one chapter, or even in a whole book for that matter. We'll cover the basics for each type of processing and then dig into a real example. By the end, you will be able to describe and use the available toolset of serverless AWS services, without having to spin up and manage your own EC2 instances. 

We'll cover the following topics:

• Types of data processing
• Building a batch processing workload—a real example
• Data analytics and transformation