Dataverse: Export-Import Solution for Virtual Table is a guide for configuring, exporting, and importing Virtual Tables from SQL databases to different environments. It starts with preparing the target database by generating scripts in SSMS and running them in a new Azure SQL DB.
The preparation of the Dataverse solution includes adding existing Virtual Tables to a new solution with the option "Include all objects". It is essential to add the corresponding Virtual Table data source and a SQL Connection Reference through the Connection Reference section.
Additional components for business logic, such as Plugin Packages and Plugin Steps, need to be included in the solution. These steps prepare the solution for export, which can then be imported into another environment through the make.powerapps.com portal with the correct SQL Server Authentication details.
After importing the solution, it is critical to update the "Virtual Connector Data Source" to adapt to the new SQL DB environment. It is also important to note that when re-importing a solution, the Dataset Value may revert to its default and needs to be manually adjusted unless the component is removed or updated separately.
Microsoft's Dataverse is an essential tool for data management and interoperability within the Power Platform ecosystem, including Dynamics 365 and Power Apps. Virtual Tables, or Virtual Entities, are a key feature, allowing seamless integration between Dataverse and external databases, such as SQL. This functionality is particularly important for organizations looking to enhance their business solution infrastructures with dynamic and interconnected systems. The ability to export and import solutions with Virtual Tables simplifies the process of maintaining consistent data across different environments, improving data accuracy and access. Developers find this feature handy to rapidly deploy and update data structures without compromising on the data already in use.
The blog post by Temmy Wahyu Raharjo delves into the intricacies of working with Virtual Tables in Microsoft Dataverse. In a previous session, they covered how to configure a Virtual Table to mirror data from an SQL Database. This time, they explore the process of preparing to export and then import this solution across different environments.
The first step in the process requires setting up the target database. Using SQL Server Management Studio (SSMS), you connect to your development database, generate scripts for the desired objects, and execute these scripts in a new Azure SQL Database. The author emphasizes the simplicity of generating scripts directly to a new query window.
Subsequently, you construct your Microsoft Dataverse solution by adding the existing Virtual Tables, ensuring that "Include all objects" is selected for table inclusion. Additionally, it's important to include the previously created Virtual Table data source, the SQL Connection Reference, and to integrate business logic crafted through plugins.
After adding the necessary components, including Plugin Packages and steps, the solution is ready for export. The import process involves navigating to the Power Apps platform, choosing the target environment, and importing the solution file. You'll be prompted to establish the connection, where you specify the SQL Server name, database, and authentication credentials.
Following the import, you must update the "Virtual Connector Data Source" to align with the new SQL Database. This entails modifying the Dataset Value within the "Advanced Settings" to reflect the target environment. Raharjo cautions that re-importing the solution may reset the Dataset Value to its original state, and manual updating might be required.
The post concludes with testing the configured plugin and a summary snapshot of the necessary components for the Microsoft Dataverse solution export-import process, note that plugins are optional. Raharjo signs off with a salute to the CRM community, underscoring their continuous learning journey and advocacy for clean, human-readable code.
Virtual Tables in Microsoft Dataverse, also known as Virtual Entities, mark a significant advancement for data integration. They allow for seamless integration of data from an external database into the Dataverse environment without the necessity for data duplication. By establishing a real-time connection, Virtual Tables enable users to work with the data as if it were natively stored in Dataverse.
This functionality supports data efficiency and reduces complexity in managing multiple data sources, thereby simplifying the application development process within the Power Platform. Moreover, it fosters a more streamlined user experience and empowers organizations to harness a broad range of data for CRM workflows, analytics, and customer insights within the familiarity of their Dataverse ecosystem.
With the export and import capabilities explained by Temmy Wahyu Raharjo, organizations can leverage these benefits across their various environments, thus enabling a consistent and scalable approach to data management and interaction across their enterprise systems.
No, virtual table data is not directly stored in Microsoft Dataverse. Virtual tables represent data that is stored outside of Dataverse, allowing you to work with the data as if it were part of Dataverse without copying or synchronizing it.
To import tables into Dataverse, you can use the Get Data feature, which supports various data sources, or you may utilize dataflows for more complex scenarios. To export tables, you can use the Export to Excel feature, or set up export profiles to move data to external systems.
Some virtual tables can be read-only or read-write, depending on how they are set up. Whether a virtual table is read-only or supports create, update, and delete operations depends on the external data source's capability and the virtual table's configuration in Dataverse.
To import data into Dataverse, you can utilize several tools such as the Data Import Wizard, Power Query, or custom code using APIs. The method chosen typically depends on the complexity of the data and the import operation required.
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