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Microsoft 365 and SharePoint Online Cookbook

Microsoft 365 and SharePoint Online Cookbook

By : Gaurav Mahajan, Sudeep Ghatak
4.5 (10)
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Microsoft 365 and SharePoint Online Cookbook

Microsoft 365 and SharePoint Online Cookbook

4.5 (10)
By: Gaurav Mahajan, Sudeep Ghatak

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)
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1
Section 1: AWS Data Engineering Concepts and Trends
6
Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
13
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning

AWS services for consuming data

Once the data has been transformed and optimized for analytics, the various data consumers in an organization need easy access to the data via a number of different types of interfaces. Data scientists may want to use standard SQL queries to query the data, while data analysts may want to both query the data in place using SQL and also load subsets of the data into a high-performance data warehouse for low-latency, high-concurrency queries and scheduled reporting. Business users may prefer accessing data via a visualization tool that enables them to view data represented as graphs, charts, and other types of visuals.

In this section, we introduce a number of AWS services that enable different types of data consumers to work with our optimized datasets. We don't cover all services that can be used to consume data in this section, but instead highlight the primary services relevant to the data engineering role.

Overview of Amazon Athena for...

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Tech Concepts
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Programming languages
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