What this book is all about
Before we wrap up this prologue and dive into more details in subsequent chapters, I want to lay the foundation for what you should expect from this book and how the content is laid out.
When you think of a data platform in an organization, it contains a lot of systems that work in tandem to make the platform operational. A data platform contains different types of purpose-built data stores, different types of ETL tools and pipelines for data movement between the data stores, different types of systems that allow end users to consume the data, and different types of security and governance mechanisms in place to keep the platform protected and safe.
To allow the data platform to cater to different types of use cases, it needs to be designed and architected in the best possible manner. With exponential data growth and the need to solve new business use cases, these architectural patterns need to constantly evolve, not just for current needs but also for future ones. Every organization is looking to move to the public cloud as quickly as they can to make their data platforms scalable, agile, performant, cost-effective, and secure.
Amazon Web Services (AWS) provides the broadest and deepest set of data, analytics, and AI/ML services. Organizations can use AWS services to help them derive insights from their data. This book will walk you through how to architect and design your data platform, for specific business use cases, using different AWS services.
In Chapter 1, we will understand what a modern data architecture on AWS looks like, and we will also look at what the pillars of this architecture are. The remainder of this book is organized around those pillars. We will start with a typical data and analytics use case and build on top of it as new use cases come along. By doing this, you will see the progressive build-up of the data platform for a variety of use cases.
One thing to note is that this book won’t have a lot of hands-on coding or other implementation exercises. The idea here is to provide architecture patterns and how multiple AWS services, along with their specific features, help solve a particular problem. However, at the end of each chapter, I will provide links to hands-on workshops, where you can follow step-by-step instructions to build the components of a modern data platform in your AWS account.
Finally, due to limited space in this book, not every use case for each of the components of the modern data platform can be covered. The idea here is to give you a simple but holistic view of what possible use cases might look like and how you can leverage some key features of many of the AWS services to get toward a working solution. A solution can be achieved in many possible ways, and every solution has pros and cons that are very specific to the implementation. Technology evolves fast and so do many of the AWS services; always do your due diligence and look out for better ways to solve problems.