NashTech Insights

Getting Data from Dynamics 365 F&O into ADF

Rahul Miglani
Rahul Miglani
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Dynamics 365 Finance and Operations stores vital business data. Extract and integrate it into Azure Data Factory for advanced analytics and reporting. Explore methods like Data Lake export, custom APIs, CDC, and Dynamics AX Connector. Leverage these methods for seamless integration and powerful insights.

Method 1: Data Lake Export

Firstly, D365 Finance and Operations offers a convenient option to export data to Azure Data Lake Storage Gen2. By leveraging this feature, you can export relevant datasets from Dynamics 365 into your designated Azure Data Lake account. Once the data is stored in Azure Data Lake, you can easily access and process it using Azure Data Factory. This approach allows for further data transformation, cleansing, or enrichment before loading it into your target data destinations.

Method 2: Custom APIs

Secondly, D365 Finance and Operations provides a flexible API framework that enables you to develop custom APIs for extracting data programmatically. Leveraging this capability, you can create custom API endpoints.Which are then used to retrieve specific data from your Dynamics instance. Azure Data Factory offers a REST connector that can be used to fetch the data from these custom APIs.

By configuring the REST connector within Azure Data Factory, you can seamlessly integrate with your custom APIs and extract the required data. This method gives you greater control over the data extraction process and allows for fine-grained data retrieval.

Method 3: Change Data Capture (CDC)

Thirdly, For real-time data integration scenarios, Dynamics 365 Finance and Operations offers Change Data Capture (CDC) mechanisms. CDC captures and records data changes in near real-time.By providing a continuous stream of updated data. Azure Data Factory can leverage CDC in Dynamics 365 Finance and Operations to ensure that your data integration processes remain up-to-date.

By monitoring the captured data changes, Azure Data Factory can ingest and sync the changed data efficiently. This method enables you to maintain synchronization between Dynamics 365 Finance and Operations and your target data destinations in real-time or near real-time.

Method 4: Dynamics AX Connector

Lastly, The Dynamics AX Connector within Azure Data Factory is specifically designed for integrating with Dynamics 365 Finance and Operations. This connector provides a simplified and streamlined approach. Very useful to extract data from Dynamics 365 Finance and Operations. It enables you to connect to your Dynamics AX instance and perform data extraction tasks seamlessly. By configuring the Dynamics AX Connector within Azure Data Factory, you can extract data from Dynamics 365 Finance and Operations tables, entities, or queries. The connector also provides built-in activities to transform, filter, or map the data as per your requirements.


In the end, Extracting data from Dynamics 365 Finance and Operations and integrating it into Azure Data Factory opens up a world of possibilities for advanced analytics, reporting, and integration with other systems. Whether you choose the Data Lake export, custom APIs, CDC, or the Dynamics AX Connector, each method offers unique advantages based on your specific needs and scenarios. By leveraging these methods, you can ensure a smooth and efficient flow of data from Dynamics 365 Finance and Operations into Azure Data Factory. All of them empowering your organization with valuable insights and enhanced data integration capabilities.

Rahul Miglani

Rahul Miglani

Rahul Miglani is Vice President at NashTech and Heads the DevOps Competency and also Heads the Cloud Engineering Practice. He is a DevOps evangelist with a keen focus to build deep relationships with senior technical individuals as well as pre-sales from customers all over the globe to enable them to be DevOps and cloud advocates and help them achieve their automation journey. He also acts as a technical liaison between customers, service engineering teams, and the DevOps community as a whole. Rahul works with customers with the goal of making them solid references on the Cloud container services platforms and also participates as a thought leader in the docker, Kubernetes, container, cloud, and DevOps community. His proficiency includes rich experience in highly optimized, highly available architectural decision-making with an inclination towards logging, monitoring, security, governance, and visualization.

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