Dataflows – Import Bulk Data or Copy Data Between Environments for Dynamics 365 and Dataverse

What is dataflow?

Dataflows are a feature of the Power Platform that allows users to extract, transform, and load data from a variety of sources. They provide a simple and efficient way to bring data into the Dataverse.

One of the key benefits of dataflows is that they allow users to perform complex data transformations without the need for coding. Using a visual interface, users can easily manipulate data by adding steps such as filters, aggregations, and data cleansing. This makes it easy for non-technical users to extract and prepare data for further analysis and reporting.

In addition to the visual interface, dataflows also provide a powerful set of data connectors that allow users to connect to a wide range of data sources. These include popular cloud services such as Salesforce, Google Sheets, and Azure SQL, as well as on-premises databases and file formats such as CSV and Excel.

Dataflows can be scheduled to run on a regular basis, allowing users to keep their data up to date and refreshed on a regular basis. This is especially useful for data sources that are constantly changing, such as CRM systems or social media platforms.

Once data has been extracted and transformed using dataflows, it can be used in a variety of ways. It can be loaded into the Dataverse for further analysis and reporting using Power BI, or used as the source for Power Apps and Power Automate to build custom business applications and automate workflows.

Licensing for Dataflows

In order to use dataflows in the Power Platform, you will need to have a valid license. The specific license required will depend on the features you want to use and the environment in which you are using dataflows.

Here are a few examples of licenses that include access to dataflows:

  • Power BI Pro: This license includes access to dataflows as well as other features of the Power BI service, such as report and dashboard creation, data visualization, and data modeling.
  • Dynamics 365 Customer Engagement Plan: This license includes access to dataflows as well as other features of the Dynamics 365 Customer Engagement platform, such as customer relationship management, sales force automation, and customer service.
  • Power Platform Plan: This license includes access to dataflows as well as other features of the Power Platform, such as Power Apps, Power Automate, and Power BI.

It’s worth noting that dataflows are also available as part of certain free plans, such as the Power BI Free plan and the Dynamics 365 Customer Engagement Free plan. However, these free plans include limited access to dataflows and other features, and may not be suitable for all use cases.

Performance tips for Dataflows

Performance is an important consideration when using Dataflows in the Power Platform. Dataflows can be resource-intensive, especially when dealing with large volumes of data or complex transformations.

Here are a few tips to help improve performance when using dataflows:

  1. Use efficient data connectors: Some data connectors are more efficient than others when it comes to extracting data. For example, using the Dataverse connector may be more efficient than using the OData connector when working with large datasets.
  2. Optimize transformations: Complex transformations can have a significant impact on dataflow performance. To improve performance, try to minimize the number of transformations you use, and consider using more efficient transformation types such as aggregations and summarizations.
  3. Use query folding: Query folding is a feature of dataflows that allows certain transformations to be pushed down to the data source, rather than being performed in the Power Platform. This can significantly improve performance, especially when working with large datasets.
  4. Monitor dataflow performance: The Power Platform provides a range of tools and metrics to help you monitor dataflow performance. These include the dataflow execution log, which provides detailed information about each step in the dataflow, as well as performance metrics such as execution time and data volume.

By following these tips, you can help ensure that your dataflows run efficiently and effectively within the Power Platform.

Use cases for Dataflows

There are many potential use cases for Power Apps dataflows, including:

  1. Data integration: Dataflows can be used to import and integrate data from various sources, such as relational databases, flat files, and cloud-based storage systems. This can be useful for organizations that need to combine data from different sources in order to perform analysis or generate reports.
  2. Data transformation: Dataflows can be used to clean, transform, and enrich data from various sources. This can include tasks such as removing duplicates, formatting data, and adding calculated columns.
  3. Data automation: Dataflows can be used to automate data preparation and integration processes, allowing organizations to save time and effort in preparing data for analysis and reporting.
  4. Data governance: Dataflows can be used to enforce data governance policies and standards, such as data quality checks and data masking.
  5. Data lake integration: Dataflows can be used to import data into Azure Data Lake Storage, allowing organizations to store and manage large volumes of data in a centralized location.
  6. Power BI integration: Dataflows can be used as a source for Power BI reports, allowing organizations to build interactive dashboards and visualizations based on data from various sources.
  7. Power Apps integration: Dataflows can be used as a source for Power Apps apps, allowing organizations to build custom business applications that are powered by data from various sources.
  8. Azure Machine Learning integration: Dataflows can be used as a source for Azure Machine Learning models, allowing organizations to build predictive models based on data from various sources.

How to start using dataflow?

  1. First, navigate to the Dataflows tab in the Power Platform and click “New dataflow”.
  2. Next, choose a data source from the list of available connectors. For example, you may choose to connect to an Excel file stored on OneDrive, a relational database or another Dynamics 365 environment.
  3. After connecting to the data source, you can use the visual interface to perform various transformations on the data. For example, you can filter rows, split columns, or apply data cleansing rules.
  4. Once you have completed your transformations, you can save and run the dataflow to extract and load the data into the Dataverse. The data can then be used in Power BI, Power Apps, or Power Automate:

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