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Microsoft 365 and SharePoint Online Cookbook
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Microsoft 365 and SharePoint Online Cookbook
By:
Overview of this book
Microsoft Office 365 provides tools for managing organizational tasks like content management, communication, report creation, and business automation processes. With this book, you'll get to grips with popular apps from Microsoft, enabling workspace collaboration and productivity using Microsoft SharePoint Online, Teams, and the Power Platform.
In addition to guiding you through the implementation of Microsoft 365 apps, this practical guide helps you to learn from a Microsoft consultant's extensive experience of working with the Microsoft business suite. This cookbook covers recipes for implementing SharePoint Online for various content management tasks. You'll learn how to create sites for your organization and enhance collaboration across the business and then see how you can boost productivity with apps such as Microsoft Teams, Power Platform, Planner, Delve, and M365 Groups. You'll find out how to use the Power Platform to make the most of Power Apps, Power Automate, Power BI, and Power Virtual Agents. Finally, the book focuses on the SharePoint framework, which helps you to build custom Teams and SharePoint solutions.
By the end of the book, you will be ready to use Microsoft 365 and SharePoint Online to enhance business productivity using a broad set of tools.
Table of Contents (19 chapters)
Preface
Section 1: AWS Data Engineering Concepts and Trends
Chapter 1: An Introduction to Data Engineering
Chapter 2: Data Management Architectures for Analytics
Chapter 3: The AWS Data Engineer's Toolkit
Chapter 4: Data Cataloging, Security, and Governance
Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
Chapter 5: Architecting Data Engineering Pipelines
Chapter 6: Ingesting Batch and Streaming Data
Chapter 7: Transforming Data to Optimize for Analytics
Chapter 8: Identifying and Enabling Data Consumers
Chapter 9: Loading Data into a Data Mart
Chapter 10: Orchestrating the Data Pipeline
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
Chapter 11: Ad Hoc Queries with Amazon Athena
Chapter 12: Visualizing Data with Amazon QuickSight
Chapter 13: Enabling Artificial Intelligence and Machine Learning
Chapter 14: Wrapping Up the First Part of Your Learning Journey
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