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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
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Author (1):
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Sinchan Banerjee Sinchan Banerjee
Author Profile Icon Sinchan Banerjee
Sinchan Banerjee
LinkedIn
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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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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

Access Control List (ACL) 232

agents

Docker agent 65

Kubelet agent 65

Aggregate Report 313

Amazon Elastic Compute Cloud (EC2) 75

Amazon Elastic Container Service (ECS) 75

Amazon Elastic Kubernetes Service (EKS) 75

Amazon Resource Name (ARN) 252

Apache Hadoop 69

Apache Kafka

setting up, on local machine 154, 155

Apache Mesos 71

Apache Spark 71

Apache Superset

about 12

URL 13

Apache YARN 71

API management

about 263

benefits 263, 264

enabling, with AWS API Gateway 264-273

architectural decision matrix

creating 337

architecture

consideration, for selecting storage 122, 123

cost factor, in processing layer 125-127

solution, building 122

storage based on cost, determining 123-125

artificial intelligence (AI) 75...

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Authors (1)

Profile icon Sinchan Banerjee
Sinchan Banerjee
LinkedIn icon
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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