Building Data Integration Solutions

Preface

This book presents a pragmatic, hands-on approach to data integration by first baselining the reader’s knowledge with important terminology and concepts and eventually walking through the building of a plausible, real-life data integration solution, step by step. For the hands-on parts in the later chapters of the book, familiarity with Linux,¹ Python, Structured Query Language (SQL), and Amazon Web Services (AWS) would be beneficial, but I’ll attempt to explain what takes place at each step in simple terms.

The combinations of tools and techniques that are described in this book are almost surely not “the best” for your specific use case. There are far too many variables and trade-offs to consider for an adequate presentation of all possible solutions. However, many of the technologies that are discussed are considered dominant players by some of the leading advisory and consultancy firms and have a significant presence within the US federal government. In this book, I prioritize the tools and technologies that meet current government mandates such as HIPAA and FedRAMP (see “Security and Compliance” for a more in-depth discussion regarding government regulations).

It should be noted that containerization is not utilized in the hands-on sections of this book. However, it may be prudent for the practitioner to use containers (e.g., Docker) and perhaps even a distributed container management tool like Kubernetes for large, enterprise data integration initiatives.

Also, while ...