Book Image

Digital Transformation with Dataverse for Teams

By : Srikumar Nair
Book Image

Digital Transformation with Dataverse for Teams

By: Srikumar Nair

Overview of this book

Microsoft Dataverse for Teams is a built-in, low-code data platform for Teams and enables everyone to easily build and deploy apps, flows, and intelligent chatbots using Power Apps, Power Automate, and Power Virtual Agents (PVA) embedded in Microsoft Teams. Without learning any coding language, you will be able to build apps with step-by-step explanations for setting up Teams, creating tables to store data, and leverage the data for your digital solutions. With the techniques covered in the book, you’ll be able to develop your first app with Dataverse for Teams within an hour! You’ll then learn how to automate repetitive tasks or build alerts using Power Automate and Power Virtual Agents. As you get to grips with building these digital solutions, you’ll also be able to understand when to consider upgrading from Dataverse for Teams to Dataverse, along with its advanced features. Finally, you’ll explore features for administration and governance and understand the licensing requirements of Microsoft Dataverse for Teams and PowerApps. Having acquired the skills to build and deploy an enterprise-grade digital solution, by the end of the book, you will have become a qualified citizen developer and be ready to lead a digital revolution in your organization.
Table of Contents (17 chapters)
1
Section 1: Introduction to Microsoft Dataverse for Teams
6
Section 2: Deep Dive into Microsoft Dataverse for Teams
10
Section 3: Application and Environment Life Cycle Management
13
Section 4: Enterprise Readiness and Licensing

Summary

In this chapter, we have seen different types of Power Automate flows – automated, instant, and scheduled flows– and the different scenarios where these could be used. We also covered some of the concepts that are often needed for building flows, such as different types of triggers – including the ones based on Dataverse, filtering datasets based on OData expressions, conditions for branching the flow of automation, adding dynamic content in flow actions such as sending messages via Teams or email, expressions to compare data, different types of connectors (Dataverse, Office 365, Teams), and corresponding actions supported by these connectors. Finally, we also saw how to test and troubleshoot common issues that you come across while creating a flow. The illustrations in this chapter do not cover the whole breadth of features and it is highly recommended that you play with additional scenarios and learn to incorporate them based on your needs.

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