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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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Toc

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

Understanding the need for data security

Before we understand the need for data security, let’s try to define what data security is. Data security is the process of protecting enterprise data and preventing any data loss from malicious or unauthorized access to data. Data security includes the following tasks:

  • Protecting sensitive data from attacks.
  • Protecting data and applications from any ransomware attacks.
  • Protecting against any attacks that can delete, modify, or corrupt corporate data.
  • Allowing access and control of data to the necessary user within the organization. Again, read-only, write, and delete access is provided to the data based on the role and its use.

Some industries may have stringent data security requirements. For example, a US health insurance company needs to ensure PHI data is extremely well protected according to HIPAA standards. Another example is that a financial firm such as Bank Of America has to ensure card and account...

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