Microsoft Dataverse Connection with Snowflake Using Matillion

This guide demonstrates how to migrate data from Microsoft Dataverse tables to Snowflake using Matillion ETL, walking through configuration steps and authentication setup.

Jul 31, 2026

Introduction

Dataverse is famous for its capability to store and manage data that is used by business applications. We can migrate the data from Dataverse tables to Snowflake using the Matillion ETL tool. This blog will guide you through the steps of how you can load data from Dataverse to Snowflake via Matillion ETL.

Step 1: Go to Microsoft 365 and search for power apps

Microsoft 365 Power Apps

Step 2: In Power Apps, click on Tables and all the available tables will be displayed

In this example, We are migrating the 'Email' table from Microsoft Dynamics 365(Dataverse) to Snowflake using Matillion ETL.

Power Apps Tables

When you select the Email table you can see the data available in that table.

Email Table Data

Step 3: Go to Matillion and perform the following steps

Step 3.1: Create an environment in Matillion by adding the following details

Add Cloud Connection details:

Cloud Connection Details

Add Snowflake Connection details:

Snowflake Connection Details

Add Snowflake Defaults:

Snowflake Defaults

Step 3.2: Adding Components to a Matillion job

Add a Component – Dynamic 365 Query to load the data from power apps (Microsoft Dataverse) to Snowflake

Dynamic 365 Query Component
Component Configuration

Setup Component Properties (Dynamics 365 Query):

Component Properties
Query Configuration

Note:
The Dynamics 365 Query connector uses an OAuth for third-party authentication.

Authentication:

Authentication Setup

Please refer to the link below for more information on authentication: Matillion Authentication Documentation

Step 4: The table 'Email' is loaded into Snowflake

Email Table Loaded

Query the Email table in the Snowflake

Snowflake Query

Conclusion

To wrap it up, the process of loading data from Dataverse to Snowflake through Matillion offers a user-friendly and efficient way to handle data.

References

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