What is Business logic in Microsoft Dataverse
Many organizations have business logic that impacts how they work with data. For example, an organization who is using Dataverse to store customer information might want to make a field such as and Identification number field required. In Microsoft Dataverse, you build this logic using business rules. Business rules allow you to apply and maintain business logic at the data layer instead of the app layer. Basically, when you create business rules in Microsoft Dataverse, those rules are in effect regardless of where users interact with the data.
For example, business rules can be used in canvas and model-driven apps to set or clear values in one or many columns in a table. They can also be used to validate stored data or show error messages. Model-driven apps can use business rules to show or hide columns, enable, or disable columns, and create recommendations based on business intelligence.
Business rules give you a powerful way to enforce rules, set values, or validate data regardless of the form that is used to input data. Business rules are also effective in helping to increase the accuracy of data, simplify application development, and streamline the forms presented to end users.
Consider this example of a simple, yet powerful use of business rules. The business rule is configured to change the field Credit Limit VP Approver to be a required field if the Credit Limit is set to greater than $1,000,000. If the credit limit is less than $1,000,000, then the field is optional.
By applying this business rule at the data level instead of the app level, you have better control of your data. This ensures your business logic is followed whether it’s being accessed directly from Power Apps, Power Automate, or even via an API. The rule is tied to the data, not the app.
To learn more about using Business rules in Dataverse, see: Create a business rule for a table.
Working with dataflows
Dataflows are self-service, cloud-based, data preparation technology. Dataflows are used to ingest, transform, and load data into Microsoft Dataverse environments, Power BI workspaces, or your organization’s Azure Data Lake Storage account. Dataflows are created using Power Query, a data connectivity and preparation experience that is already included in many Microsoft products, such as Excel and Power BI. Customers can trigger dataflows to run either on demand or automatically on a schedule, data is always kept up to date.
Because a dataflow stores the resulting entities in cloud-based storage, other services can interact with the data produced by dataflows.
For example, Power BI, Power Apps, Power Automate, Power Virtual Agents, and Dynamics 365 applications can get the data produced by the dataflow by connecting to Dataverse, a Power Platform dataflow connector. Alternatively, they can get the data directly through the lake, depending on the destination configured at dataflow creation time.
The following list highlights some of the benefits of using dataflows:
- A dataflow decouples the data transformation layer from the modeling and visualization layer in a Power BI solution.
- The data transformation code can reside in a central location, a dataflow, rather than be spread out among multiple artifacts.
- A dataflow creator only needs Power Query skills. In an environment with multiple creators, the dataflow creator can be part of a team that together builds the entire BI solution or operational application.
- A dataflow is product agnostic. It’s not a component of Power BI only, as you can get its data in other tools and services.
- Dataflows take advantage of Power Query, a powerful, graphical, self-service data transformation experience.
- Dataflows run entirely in the cloud. No other infrastructure is required.
- You have multiple options for starting to work with dataflows, using licenses for Power Apps, Power BI, and Customer Insights.
- Dataflows are capable of advanced transformations, but they’re designed for self-service scenarios and require no IT or developer background.