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

We started this chapter by learning how to plan and estimate infrastructure resources. Then, we discussed how to do an effort estimation, how to load human resources, and how to calculate the total development cost. By doing so, we learned how to create an architectural decision matrix and how to perform data-driven comparisons between different architectures. Then, we delved into the different ways we can use the decision matrix to evaluate the most optimal solution by using spider/radar charts or decision trees. Finally, we discussed some guidelines and tips for presenting the optimized solution in a more effective and impactful way to various business stakeholders.

Congratulations – you have completed all 12 chapters of this book, where you learned all about a Java data architect’s role, the basics of data engineering, how to build solutions for various kinds of data engineering problems, various architectural patterns, data governance and security, and...