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  • Book Overview & Buying Microsoft 365 and SharePoint Online Cookbook
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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

The rise of big data as a corporate asset

You don't need to look too far or too hard these days to hear about how big data and data analytics are transforming organizations and having an impact on society as a whole. We hear about how companies such as TikTok analyze large quantities of data to make personalized recommendations about which clip to show a user next. Also, we know how Amazon recommends products a customer may be interested in based on their purchase history. We read headlines about how big data could revolutionize the healthcare industry, or how stock pickers turn to big data to find the next breakout stock performer when the markets are down.

The most valuable companies in the US today are companies that are masters of managing huge data assets effectively, with the top five most valuable companies in Q4 2021 being the following:

  • Microsoft
  • Apple
  • Alphabet (Google)
  • Amazon
  • Tesla

For a long time, it was companies that managed natural gas and oil resources, such as ExxonMobil, that were high on the list of the most valuable companies on the US stock exchange. Today, ExxonMobil will often not even make the list of the top 30 companies. It is no wonder that the number of job listings for people with skillsets related to big data is on the rise.

There is also no doubt that data, when harnessed correctly and optimized for maximum analytic value, can be a game-changer for an organization. At the same time, those companies that are unable to effectively utilize their data assets risk losing a competitive advantage to others that do have a comprehensive data strategy and effective analytic and machine learning programs.

Organizations today tend to be in one of the following three states:

  • They have an effective data analytics and machine learning program that differentiates them from their competitors.
  • They are conducting proof of concept projects to evaluate how analytic and machine learning programs can help them achieve a competitive advantage.
  • Their leaders are having sleepless nights worrying about how their competitors are using analytics and machine learning programs to achieve a competitive advantage over them.

No matter where an organization currently is in their data journey, if they have been in existence for a while, they have likely faced a number of common data-related challenges. Let's look at how organizations have typically handled the challenge of ever-growing datasets.

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