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Learn Microsoft Fabric

You're reading from   Learn Microsoft Fabric A practical guide to performing data analytics in the era of artificial intelligence

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781835082287
Length 338 pages
Edition 1st Edition
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Authors (2):
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Bradley Schacht Bradley Schacht
Author Profile Icon Bradley Schacht
Bradley Schacht
Arshad Ali Arshad Ali
Author Profile Icon Arshad Ali
Arshad Ali
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Table of Contents (19) Chapters Close

Preface 1. Part 1: An Introduction to Microsoft Fabric FREE CHAPTER
2. Chapter 1: Overview of Microsoft Fabric and Understanding Its Different Concepts 3. Chapter 2: Understanding Different Workloads and Getting Started with Microsoft Fabric 4. Part 2: Building End-to-End Analytics Systems
5. Chapter 3: Building an End-to-End Analytics System – Lakehouse 6. Chapter 4: Building an End-to-End Analytics System – Data Warehouse 7. Chapter 5: Building an End-to-End Analytics System – Real-Time Analytics 8. Chapter 6: Building an End-to-End Analytics System – Data Science 9. Part 3: Administration and Monitoring
10. Chapter 7: Monitoring Overview and Monitoring Different Workloads 11. Chapter 8: Administering Fabric 12. Part 4: Security and Developer Experience
13. Chapter 9: Security and Governance Overview 14. Chapter 10: Continuous Integration and Continuous Deployment (CI/CD) 15. Part 5: AI Assistance with Copilot Integration
16. Chapter 11: Overview of AI Assistance and Copilot Integration 17. Index 18. Other Books You May Enjoy

Summary

The importance of real-time data cannot be overstated. It can mean a more reliable business function, a competitive edge, or an experience not previously possible. Fabric’s Real-Time Analytics enables organizations to collect data from sources such as IoT devices and telemetry through eventstreams or land large datasets using tools such as Data Factory.

The RTA experience is the perfect solution for analyzing billions or even trillions of records in seconds. With seamless integration to expose data in OneLake, you can take the same data from a KQL database and consume it through shortcuts in a lakehouse to create new data products and extend the analytics using Spark.

In this chapter, you learned how to create an end-to-end real-time analytics solution. You learned how to create a KQL database, use an eventstream to load real-time stock ticker data into the database, use the Kusto Query Language to explore and analyze the data, and use this data stream in a Power...

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