Book Image

Scalable Data Architecture with Java

By : Sinchan Banerjee
Book Image

Scalable Data Architecture with Java

By: Sinchan Banerjee

Overview of this book

Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data. This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert. You’ll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you’ll understand how to architect a batch and real-time data processing pipeline. You’ll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you’ll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics. By the end of this book, you’ll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.
Table of Contents (19 chapters)
1
Section 1 – Foundation of Data Systems
5
Section 2 – Building Data Processing Pipelines
11
Section 3 – Enabling Data as a Service
14
Section 4 – Choosing Suitable Data Architecture

Summary

In this chapter, we learned what data engineering is and looked at a few practical examples of data engineering. Then, we covered the basics of data engineering, including the dimensions of data and the kinds of problems that are solved by data engineers. We also provided a high-level overview of various kinds of processing problems and publishing problems in a data engineering landscape. Then, we discussed the roles and responsibilities of a data architect and the kind of challenges they face. We also briefly covered the way this book will guide you to overcome challenges and dilemmas faced by a data architect and help you become a better Java data architect.

Now that you understand the basic landscape of data engineering and what this book will focus on, in the next chapter, we will walk through various data formats, data storage options, and databases and learn how to choose one for the problem at hand.