Microsoft Dataverse is a powerful data platform that supports secure and scalable data storage for business applications. However, raw data imported into Dataverse often needs transformation—cleaning, reshaping, filtering, or merging—to make it useful and reliable for apps and analytics.  In this blog, we’ll show you how to apply transformations to data before or after it reaches Dataverse using tools like Power Query, Dataflows, and business rules—ensuring you always work with clean, structured, and actionable data.  What is Data Transformation in Dataverse?  Why Data Transformation Matters Data transformation refers to modifying data’s structure, content, or format before or after it’s stored in Dataverse. This includes:  Step-by-Step Guide: Connecting a Database to Dataverse  Step 1: Open the Power Apps and select the proper Environment  Step 2: Open Dataflow in Power Apps and create a new Dataflow  Step 3: Connect to the Database using SQL Server Database.  Step 4: Add the required credentials to make the connection between the database and Dataverse.  Step 5: Add the transformation in the Dataverse  Step 6: Add proper mapping of the column and find the unique ID of the table   Step 7: Set the schedule refresh and publish the Dataflow.  Step 8: Once Dataflow is published, we can see the table in the Power apps  To conclude, transforming data in Dataverse is key to building reliable and high-performing applications. Whether using Power Query, calculated columns, or Power Automate, you can ensure your data is clean, structured, and actionable.  We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfonts.com. Ready to improve your Dataverse data quality? Start with a simple dataflow or calculated column today, and empower your business applications with better, transformed data.

Integration platforms are critical to modern business operations, allowing different applications, data, and systems to communicate effectively. While both serve the purpose of integration, they cater to different needs and scenarios. In this blog, we’ll compare BizTalk and Azure Logic Apps, helping you choose the right platform for your business. Outline 1. Opening Section: 2. Introduction: 3. Core Content: Key Differences Between BizTalk and Azure Logic Apps: When to Choose BizTalk Server: When to Choose Azure Logic Apps: 4. Conclusion and CTA: In conclusion, BizTalk Server and Azure Logic Apps cater to different integration needs. While BizTalk excels in enterprise-grade, on-premises scenarios, Azure Logic Apps shines in cloud-native, modern workflows. Choosing the right platform depends on your organization’s integration requirements, scalability goals, and budget. CTA: If you’re still unsure which platform aligns best with your needs, our team of integration experts can help. Contact us for a detailed assessment and tailored recommendations for your business integration journey. Let’s streamline your operations and drive growth together