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Stream Analytics with Microsoft Azure

You're reading from  Stream Analytics with Microsoft Azure

Product type Book
Published in Dec 2017
Publisher Packt
ISBN-13 9781788395908
Pages 322 pages
Edition 1st Edition
Languages
Authors (2):
Ryan Murphy Ryan Murphy
Profile icon Ryan Murphy
Manpreet Singh Manpreet Singh
Profile icon Manpreet Singh
View More author details
Toc

Table of Contents (18) Chapters close

Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Introducing Stream Processing and Real-Time Insights 2. Introducing Azure Stream Analytics and Key Advantages 3. Designing Real-Time Streaming Pipelines 4. Developing Real-Time Event Processing with Azure Streaming 5. Building Using Stream Analytics Query Language 6. How to achieve Seamless Scalability with Automation 7. Integration of Microsoft Business Intelligence and Big Data 8. Designing and Managing Stream Analytics Jobs 9. Optimizing Intelligence in Azure Streaming 10. Understanding Stream Analytics Job Monitoring 11. Use Cases for Real-World Data Streaming Architectures

Summary


Following is a quick summary of topics we covered in this chapter. We reviewed what is Azure Stream Analytics, understood its key advantages in terms of developer productivity, ease of development and how to reduces total cost of ownership, global compliance certifications, the value of the PaaS based streaming solution to host mission-critical applications and briefly reviewed security.  

Now that we have a basic understanding of Azure Stream Analytics in the next chapter we will explore how to start building a Streaming pipeline, look into deployment, logging and monitoring, and finally review sample use cases to consolidate our learnings.

 

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