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

Building an effective data model

From our previous discussion and after analyzing the data, we have concluded that our data is structured, so it’s suitable for being stored in a relational data model. From the requirements, we have gathered that our final data store should be a data warehouse. Keeping these two basic factors in mind, let’s learn about relational data warehouse schemas.

Relational data warehouse schemas

Let’s explore the popular relational data warehouse schemas that we can consider when creating our data model:

  • Star schema: This is the most popular data warehouse schema type. As shown in the following diagram, there is a Fact Table in the middle where each record represents a fact or an event that has happened over time:

Figure 4.8 – Star schema

This Fact Table consists of various dimensions whose details need to be looked up from associated lookup tables called dimension tables. This Fact Table...