Create and Manage Model-Driven Apps with Power Apps and Dataverse

Duration

1 day

Overview

In this learning path, you practice building model-driven apps by using Microsoft Power Apps. The skills validated include creating Dataverse tables, modifying forms and views, and configuring a model-driven app. The scenario in this experience represents real-world challenges faced by individuals with business-specific expertise who build model-driven apps.

Prerequisites

Candidates for this credential should be familiar with data modeling concepts in Microsoft Dataverse and with the Power Apps maker portal.

Outlines

Introduction to Microsoft Dataverse

Data is at the center of everything a business does today and powers the insights that can drive what it should do tomorrow. To thrive and grow, businesses need to capture, analyze, predict, present, and report data and do it all with a high level of agility.

A business may have many data sources across various devices, applications, systems, and software as a service (SaaS) providers. There may be connectors for some or all of these data sources to allow you to build apps and flows by using the Microsoft Power Platform, but these data stores need to be managed and require different tools, skills, and security models.

Microsoft Dataverse

Microsoft Dataverse is the cloud data platform for the Microsoft Power Platform that is easy to use, compliant, secure, scalable, and globally available. Using Microsoft Dataverse as the data store for your apps has many benefits:

• Metadata: Properties you define on your data model are used by Power Apps, speeding up the building of apps.
• Data access: You can control who can access which tables, rows, and columns.
• Logic: Calculations and rules can be added to table columns.
• Import and export: You can choose from multiple tools to manage your data, including Excel.
• Audit: You can track who accesses and changes data.
• Processes: Business processes can be added to ensure data quality and perform automation.
• Managed data in the cloud: You don't need to perform backups or configure the database because this is performed for you by Microsoft.
• Storage: You don't need to worry about how the data is stored because Microsoft takes care of this for you.
• Skills: You don't need to be a DBA to manage Dataverse.
• Secure: All data is encrypted at rest and in transit.
• Integration: Dataverse is deeply integrated with Microsoft cloud services such as Microsoft 365 and Microsoft Azure.
• Proven: Microsoft Dataverse is used by Dynamics 365 apps such as Dynamics 365 Sales and Dynamics 365 Customer Service.
• Connectors: Microsoft Dataverse has connectors for Power Apps, Power Automate, and Power BI.

Table characteristics

Data within Dataverse is stored within a set of records called tables. A table is a logical structure of rows and columns that represent a set of data, similar to how a table stores data within a database.

Tables represent objects or things of the internet. These can be physical things such as pets, buildings, and products, or abstract concepts such as projects, skills, and benefits.

Microsoft Dataverse is designed to let you quickly and easily create a data model for your application, based on the tables and the table metadata that you include in your app.

Dataverse includes a base set of standard tables that support common business scenarios. You can also create custom tables specific to your organization and populate them with data that you import from lists in Microsoft SharePoint, from Microsoft Excel, or by using PowerQuery. App makers can then use Power Apps to build rich applications by using this data.

Create a Microsoft Dataverse table

To create a Dataverse table, select on Tables in left-hand navigation of the Power Apps maker portal, and then select the New table dropdown. You have several different options to create a Dataverse table.

Start from a blank table

• Add columns and data: Create a table by entering the data rows and columns you want.
• Describe the new table: Create a table with the help of AI Copilot. Tell Copilot what you want and watch it build the table for you.
• Set advanced properties: Start with a blank table and enter the table properties, such as name, and description. Expand Advanced options to set more properties, such as track changes and audit changes.

Use existing data

• Create with external data: Use an Excel or CSV file to populate a table with your data, which uses AI to assist with the table generation when copilot is enabled for the environment. You can also use an existing SharePoint list.
• Create a virtual table: A virtual table is a custom table in Microsoft Dataverse that has columns containing data from an external data source, such as Azure SQL Database.

Import data into your Microsoft Dataverse database

• Create sample import data
• Import data into your Dataverse table

Table relationships

• Relationship types
• Many-to-one vs. One-to-many
• Create table relationships manually

Dataverse logic and security

Microsoft Dataverse is more than a data store, it contains features to apply business logic to data and securing access to data.

Tables within Dataverse can use rich server-side logic and validation to ensure data quality. You can also reduce repetitive code in each app that creates and uses data within a table.

• Business rules: Business rules validate data across multiple columns in a table, and provide warning and error messages, regardless of the app that's used to create the data.
• Business process flows: Business process flows guide users to ensure they enter data consistently and follow the same steps every time. Business process flows are currently supported only for model-driven apps.
• Real-time workflows: Workflows automate business processes without requiring user interaction.
• Business logic with code: Business logic supports advanced developer scenarios that extend the application directly through code.

Dataverse auditing

Microsoft Dataverse supports an auditing feature designed to meet the external and internal auditing, compliance, security, and governance policies that are common to many enterprises. Dataverse auditing logs changes that are made to customer records in an environment with a Dataverse database. Dataverse auditing also logs user access through an app or through the SDK in an environment.

Dataverse auditing is supported on all custom and most customizable tables and columns. Audit logs are stored in Dataverse and consume log storage capacity. You can view audit logs in the Audit History tab for a single record. You can view audit logs in the Audit Summary view for all audited operations in a single environment. Audit logs can also be retrieved using the Web API or the Organization Service.

Dual-write vs. virtual tables

Microsoft Dataverse allows for many different connections to external data sources. Dual-write and virtual entities allow Dataverse to access this data and write back to the original data source. The purpose of this unit is to help you understand a bit about these exciting capabilities.

Summary

Dataverse lets you securely store and manage data that's used by business applications. This data is usable across the Power Platform. Standard and custom tables within Dataverse provide a secure and cloud-based storage option for your data.

Programme scope, delivery arrangements and suitability are confirmed during enquiry.