February 2024
Beginner to intermediate
367 pages
6h 51m
English
Overview
Learn and explore the capabilities of Microsoft Fabric, the latest evolution in cloud analytics suites. This book will help you understand how users can leverage Microsoft Office equivalent experience for performing data management and advanced analytics activity.
The book starts with an overview of the analytics evolution from on premises to cloud infrastructure as a service (IaaS), platform as a service (PaaS), and now software as a service (SaaS version) and provides an introduction to Microsoft Fabric. You will learn how to provision Microsoft Fabric in your tenant along with the key capabilities of SaaS analytics products and the advantage of using Fabric in the enterprise analytics platform. OneLake and Lakehouse for data engineering is discussed as well as OneLake for data science. Author Ghosh teaches you about data warehouse offerings inside Microsoft Fabric and the new data integration experience which brings Azure Data Factory and Power Query Editor of Power BI together in a single platform. Also demonstrated is Real-Time Analytics in Fabric, including capabilities such as Kusto query and database. You will understand how the new event stream feature integrates with OneLake and other computations. You also will know how to configure the real-time alert capability in a zero code manner and go through the Power BI experience in the Fabric workspace. Fabric pricing and its licensing is also covered.
After reading this book, you will understand the capabilities of Microsoft Fabric and its Integration with current and upcoming Azure OpenAI capabilities.
What You Will Learn
- Build OneLake for all data like OneDrive for Microsoft Office
- Leverage shortcuts for cross-cloud data virtualization in Azure and AWS
- Understand upcoming OpenAI integration
- Discover new event streaming and Kusto query inside Fabric real-time analytics
- Utilize seamless tooling for machine learning and data science
Who This Book Is For
Citizen users and experts in the data engineering and data science fields, along with chief AI officers
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