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Scalable Data Architecture with Java

You're reading from   Scalable Data Architecture with Java Build efficient enterprise-grade data architecting solutions using Java

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781801073080
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Sinchan Banerjee Sinchan Banerjee
Author Profile Icon Sinchan Banerjee
Sinchan Banerjee
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Table of Contents (19) Chapters Close

Preface 1. Section 1 – Foundation of Data Systems
2. Chapter 1: Basics of Modern Data Architecture FREE CHAPTER 3. Chapter 2: Data Storage and Databases 4. Chapter 3: Identifying the Right Data Platform 5. Section 2 – Building Data Processing Pipelines
6. Chapter 4: ETL Data Load – A Batch-Based Solution to Ingesting Data in a Data Warehouse 7. Chapter 5: Architecting a Batch Processing Pipeline 8. Chapter 6: Architecting a Real-Time Processing Pipeline 9. Chapter 7: Core Architectural Design Patterns 10. Chapter 8: Enabling Data Security and Governance 11. Section 3 – Enabling Data as a Service
12. Chapter 9: Exposing MongoDB Data as a Service 13. Chapter 10: Federated and Scalable DaaS with GraphQL 14. Section 4 – Choosing Suitable Data Architecture
15. Chapter 11: Measuring Performance and Benchmarking Your Applications 16. Chapter 12: Evaluating, Recommending, and Presenting Your Solutions 17. Index 18. Other Books You May Enjoy

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...

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