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Azure Integration Guide for Business

You're reading from   Azure Integration Guide for Business Master effective architecture strategies for business innovation

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781837639144
Length 268 pages
Edition 1st Edition
Tools
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Authors (4):
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Trevoir Williams Trevoir Williams
Author Profile Icon Trevoir Williams
Trevoir Williams
Jack Lee Jack Lee
Author Profile Icon Jack Lee
Jack Lee
Mélony Qin Mélony Qin
Author Profile Icon Mélony Qin
Mélony Qin
Joshua Garverick Joshua Garverick
Author Profile Icon Joshua Garverick
Joshua Garverick
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Toc

Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Unlock New Opportunities with Azure FREE CHAPTER 2. Chapter 2: Achieve Availability, Scalability, and Monitoring with Azure 3. Chapter 3: Cloud Architecture Design Patterns 4. Chapter 4: Azure Network Infrastructure and Design 5. Chapter 5: Automating Architecture on Azure 6. Chapter 6: Optimize Performance with Azure OLTP Solutions 7. Chapter 7: Designing Serverless Architecture Solutions in Azure 8. Chapter 8: Deploying, Managing, and Scaling Containers with Azure Kubernetes Service 9. Chapter 9: Designing Big Data Solutions with Azure 10. Chapter 10: Architecting Secure Applications on a Trusted Platform 11. Chapter 11: Cost Governance on Azure 12. Chapter 12: Conclusion 13. Index 14. Other Books You May Enjoy

Summary

In this chapter, you gained an understanding of the application architecture for creating big data and intelligent solutions using Azure technologies. Azure provides several services and integrations that assist in developing big data pipelines that can ingest data in various forms and from different sources, consolidate the data, and ultimately convert it into a more acceptable form for human consumption. We can then build dashboards and visualizations using powerful tools, such as Power BI.

We then must consider that data might not always be from static sources, such as databases or files, but it might come in varied volumes and velocities from smart devices. These devices can send data based on different parameters, and the data might not be standardized or structured. In this case, we use IoT solutions and messaging systems to handle and react to the incoming event data from these devices.

After figuring out how to collate and aggregate big data, we need to apply...

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