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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

Product type Paperback

Published in Sep 2022

Publisher Packt

ISBN-13 9781801073080

Length 382 pages

Edition 1st Edition

Languages

Java

Tools

Deeplearning4j

Concepts

Data Science

Author (1):

Sinchan Banerjee

View More author details

Table of Contents (19) Chapters

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

Why subscribe?

18. Other Books You May Enjoy

Technical requirements

For this chapter, you will need the following:

Prior knowledge of Java
OpenJDK-1.11 installed on your local system
Maven installed on your local system
GraphQL Playground installed on your local system
IntelliJ Idea community or ultimate edition installed on your local system

The code for this chapter can be downloaded from this book’s GitHub repository: https://github.com/PacktPublishing/Scalable-Data-Architecture-with-Java/tree/main/Chapter10.

The rest of the chapter is locked

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Authors (1)

Sinchan Banerjee

Sinchan Banerjee

Sinchan Banerjee is a Principal Data architect who has vast experience in architecting, building and leading multiple data engineering solutions in healthcare and finance domain. His expertise lies in architecting, designing, developing, and delivering high volume fast paced data engineering solutions using cutting-edge Big Data and Streaming technologies over cloud platforms like AWS, Azure and OpenShift, and on-premises. He has rich experience in designing, building and deploying microservices using SOAP, REST and GraphQL over Kubernetes and Docker in the cloud platforms as well as in on-premises. He has also considerable experience in creating proposal, present and enables to win multimillion dollar business deals for his employer. He is currently a Principal Data architect at UST Inc working for their client ElevanceHealth (Formerly Anthem) and leading Anthem's digitalization journey into cloud. Prior to this, he has worked for multiple organizations as a Data architect at American Express, Data-core Systems Inc., UnitedHealth Group and as data engineer at Impetus and Hewlett-Packard. He has a bachelor's degree in Computer Science and Engineering from SRM University and is certified in Machine learning with Big Data Analytics from University of California. He is also a certified AWS professional and a certified Java programmer. He is the lead inventor of a patent (on Storage Capacity Forecasting using Predictive Analysis and has co-authored multiple international publications. He is the recipient of multiple awards and accolades throughout his career from multiple organizations like Hewlett-Packard, UnitedHealth Group and UST, for his technical contribution, innovation, and leadership skills. He currently resides in the United States along with his family and pets.

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