The Power of Dataflows to Import and Transform Data in Power Platform
- Marco P.
- Jun 6
- 3 min read
Managing and integrating large volumes of data is a key challenge in any digital transformation project. In the Microsoft Power Platform ecosystem, Dataflows are one of the most powerful and underutilized tools for importing, transforming, and centralizing data into Dataverse and other storage systems.
Whether you're pulling data from external systems, cleaning and reshaping it, or loading it into Dataverse for use in Power Apps or Power BI, Dataflows offer a scalable and efficient way to make your data work for you.
⚙️ What Are Dataflows?
Dataflows are cloud-based, reusable data transformation pipelines built on Power Query, the same technology used in Excel and Power BI. They allow you to connect to various data sources, cleanse, transform, and load data into Dataverse or Azure Data Lake.
Think of them as ETL (Extract, Transform, Load) tools for Power Platform—no code required, yet extremely flexible and powerful.
🚀 Why Dataflows Are So Powerful
1. Handle Large Volumes of Data
Dataflows are optimized to work with large datasets from on-premises or cloud-based systems. They are ideal for batch data ingestion, reducing the need for custom scripts or manual file imports.
2. Automated, Scheduled Imports
You can schedule refreshes of your Dataflows to keep your data in sync automatically—daily, hourly, or even multiple times a day.
3. Transform Before Loading
With built-in Power Query, you can:
Filter and clean data
Merge tables and columns
Apply business logic
Rename or restructure fieldsAll before the data even hits Dataverse, ensuring your environment is clean and optimized.
4. Centralized Data Logic
By storing transformation logic in a centralized dataflow, you eliminate the need to duplicate logic across multiple apps or flows, simplifying governance and maintenance.
5. Integration with Multiple Sources
Dataflows support a wide range of data sources:
Excel / CSV files
SQL Server, Oracle, MySQL
SharePoint lists
Dynamics 365
Salesforce
Web APIs…and more.
🧪 Common Use Cases
Importing master data like products, customers, or locations into Dataverse
Syncing data from legacy databases to Power Platform
Preparing data for analytics in Power BI
Cleaning up Excel files from different departments before using them in apps
Consolidating data from multiple systems into a single model
⚠️ Known Limitation: Business Unit Assignment
One key limitation of Dataflows is that you cannot directly assign records to a specific Business Unit during the import into Dataverse. All records will inherit the Business Unit of the user running the dataflow.
However, there's a practical workaround:
During transformation, you can identify or retrieve the GUID (ID) of the Business Unit you want each record to belong to.
After import, you can use Power Automate to run a background process that assigns each record to the correct Business Unit using that ID.
While this adds an extra step, it ensures your data respects your organization’s structure and security model.
🛠️ How to Use Dataflows in Power Platform
Navigate to Power Apps or Power BI Service
Go to Data > Dataflows
Click New Dataflow and choose a source (e.g., Excel, SQL, API)
Use Power Query to transform the data
Choose your destination: Dataverse or Azure Data Lake
Set a refresh schedule
Save and monitor execution from the Dataflows page
🧠 Final Thoughts
Dataflows are a must-have tool for any organization working with data at scale in the Power Platform. They allow business users and developers to bring data into the platform in a clean, structured, and automated way, enabling better decision-making and more powerful applications.
Despite some limitations—like the inability to directly assign Business Units—Dataflows combined with Power Automate can help you build reliable, scalable, and secure data pipelines for your apps.
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