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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 problem and source data

Data engineering often involves collecting, storing, and analyzing data. But nearly all data engineering landscapes start with ingesting raw data into a data lake or a data warehouse. In this chapter, we will be discussing one such typical use case and build an end-to-end solution for the problem discussed in the following section.

Problem statement

Company XYZ is a third-party vendor that provides services for building and maintaining data centers. Now, Company XYZ is planning to build a data center monitoring tool for its customer. The customer wants to see various useful metrics, such as the number of incidents reported for any device on an hourly, monthly, or quarterly basis. They also want reports on closure ratios and average closure duration. They are also interested in searching incidents based on the type of device or incident type. They are also interested to find time-based outage patterns to predict seasonal or hourly usage...

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