Importing and exporting data
There are multiple ways to import and export data into Microsoft Dataverse. You can use dataflows, Power Query, Azure Data Factory, Azure Logic Apps, and Power Automate.
Dynamics customers also have access to the Data Export Service.
Dataflows and Power Query
Dataflows enable you to connect with business data from various sources, clean the data, transform it, and then load it into Dataverse. Dataflows support dozens of popular on-premises, cloud, and software as a service (SaaS) data sources.
Power Query is a data connection technology you can use to discover, connect, combine, and refine data sources to meet your analysis needs. Features in Power Query are available in Excel and Power BI Desktop.
More information: Create and use dataflows in Power Apps and Add data to a table in Dataverse by using Power Query
Azure Data Factory
Data Factory is a data integration service that provides a low-code or no-code approach to construct extract, transform, and load (ETL) processes within a visual environment or by writing your own code.
With Data Factory, you can visually integrate Dataverse and other data sources by using more than 90 natively built and maintenance-free connectors.
In addition to bringing data into Dataverse, Data Factory can also be used to prepare, transform, and enrich data with Databricks and move data into Azure Synapse Analytics.
Exporting data from Dataverse
Exporting data, either to another data technology or to another Dataverse environment, can use any of the same technologies mentioned for importing data, such as dataflows, Data Factory, Power Query, and Power Automate.
Dynamics customers who are targeting SQL Server or Azure SQL Database can use the Data Export Service. This is an add-on service made available as a Dataverse solution that adds the ability to replicate Dataverse data to a SQL Database store in a customer-owned Azure subscription. The supported target destinations are SQL Database and SQL Server on Azure virtual machines. Data Export Service intelligently synchronizes the entire Common Data Service schema and data initially and, thereafter, synchronizes on a continuous basis as changes occur (delta changes) in Dataverse.