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Microsoft 365 and SharePoint Online Cookbook

Microsoft 365 and SharePoint Online Cookbook

By : Mahajan, Sudeep Ghatak, Nate Chamberlain, Scott Brewster
4.8 (23)
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Microsoft 365 and SharePoint Online Cookbook

Microsoft 365 and SharePoint Online Cookbook

4.8 (23)
By: Mahajan, Sudeep Ghatak, Nate Chamberlain, Scott Brewster

Overview of this book

Microsoft 365 offers tools for content management, communication, process automation, and report creation. Microsoft 365 and SharePoint Online Cookbook maximizes workplace collaboration and productivity using SharePoint Online, Teams, OneDrive, Delve, M365 Search, Copilot, Power Platform, Viva, Planner, and Microsoft Forms. You will find thoroughly updated recipes for SharePoint Online, covering sites, lists, libraries, pages, web parts, and learn SharePoint Framework (SPFx) basics for building solutions. You will explore many Microsoft Teams recipes to prepare it to be your organization’s central collaboration hub. You will be able to unlock Power Platform potential with recipes for Power Apps to enable low-code/no-code app development and learn to automate tasks with Power Automate and Power Automate Desktop. The book teaches you data visualization with Power BI, and chatbot creation with Power Virtual Agents (Copilot Studio). Finally, you will also learn about the cutting-edge Copilot and Gen AI functionality in Microsoft 365 and Power Platform. By the end, you will be equipped with skills to effectively use Microsoft 365, SharePoint Online, and the Power Platform. Whether it's enhancing career prospects or improving business operations, this book is a perfect companion on your journey through the Microsoft Office 365 suite.
Table of Contents (15 chapters)
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Index

Transforming data

Data transformation refers to the process of converting data from one format to another. This could require simple or complex data manipulation, based on the nature of the data.

In most cases, the data that you retrieve from a data source is not in a format where it can be used as-is, and you might have to take some additional steps to clean it.

Examples of basic transformations include the following:

  • Changing data types
  • Filtering (rows and/or fields)
  • Creating conditional columns
  • Splitting columns
  • Renaming/reformatting

Some examples are as follows:

  • Getting rid of trailing spaces at the end of a text field
  • Reconciling multiple formats saved in a date field (such as Jan-19, Jan 2019, 01-19, and so on)
  • Concatenating Title, First Name, Last Name, and so on to get the person's name

Hence, the first step after retrieving data from a data store is to clean the data and convert it into a reusable format. In the following example, we will perform three data transformation...

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