Introduction
Organizations rely heavily on CRM platforms like Salesforce to manage customer relationships, sales pipelines, marketing campaigns, and operational activities. However, deriving meaningful insights from Salesforce data often requires integrating it with enterprise analytics platforms.
With Microsoft Fabric, organizations can unify data engineering, real-time analytics, business intelligence, and AI into a single SaaS platform. One of the simplest and most powerful ways to ingest Salesforce data into Fabric is through Dataflow Gen2.
In this article, we will walk through how to seamlessly connect Salesforce to Microsoft Fabric using Dataflow Gen2 and ingest CRM data into a Lakehouse for downstream analytics and reporting.
Why Integrate Salesforce with Microsoft Fabric?
Integrating Salesforce into Fabric enables organizations to:
Centralize CRM data into a modern data platform
Eliminate manual CSV exports and siloed reporting
Build near real-time dashboards in Power BI
Enable advanced analytics and AI on customer data
Support Medallion Architecture (Bronze, Silver, Gold)
Create a single source of truth across departments
Why Use Dataflow Gen2?
Dataflow Gen2 is Microsoft Fabric’s modern low-code/no-code data ingestion and transformation service.
Key benefits include:
✔ Native connectors for cloud applications like Salesforce
✔ Built-in Power Query transformation engine
✔ Supports scheduled refresh and automation
✔ Easy loading into Lakehouse or Warehouse
✔ Minimal coding required
✔ Enterprise-grade scalability
Solution Architecture
The architecture for this integration looks like this:
Salesforce CRM
│
▼
Dataflow Gen2 Connector
│
▼
Power Query Transformations
│
▼
Fabric Lakehouse (Bronze)
│
▼
Fabric Warehouse / Power BI
Prerequisites
Before starting, ensure you have:
1. Microsoft Fabric Workspace
A Fabric-enabled workspace with appropriate permissions.
2. Salesforce Account
Access to Salesforce with API permissions enabled.
3. Dataflow Gen2 Access
Permission to create and manage Dataflows in Fabric.
4. Destination Lakehouse
Create a target Lakehouse where Salesforce tables will be loaded.
Salesforce Objects We Will Ingest
For this demo, we will extract Contact object in the salesforce CRM platform
Expected Outcome
At the end of this implementation, you will have:
Salesforce data landing automatically in Fabric
Tables available in your Lakehouse
Data ready for SQL analytics
Power BI dashboards built on top
A repeatable ingestion pipeline
Next Step-by-Step Implementation
This article assumes you have set-up your salesforce account. You can proceed to this link to create a 30 days free trial: Starter Suite Free Trial: Get Started | Salesforce UK
In the Salesforce free trial page, provide your details accordingly and you would receive an email in your provided email address containing verification and your username. Note, you can perfectly use email such as gmail, yahoo, outlook to create the free trial account. You don't necessary have to use work email
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In the screenshot below, I have Contact object in my Salesforce account with two records. To ingest csv data into the contact object for example, click the Import and follow the onscreen instruction.
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In Microsoft Fabric as seen in the screenshot below, I created an instance of Dataflow Gen 2 item to kick-off the data integration
![2]()
In the Get data drop-down, searched for salesforce objects connector
![3]()
If you successfully created a free salesforce trial account, you would have received an email from salesforce containing your username. Copy the username.
In connect to data source, click sign-in and a salesforce login window pops-up to provide your username and salesforce password. Provide those login details. In this article, I successfully logged in.
Click Next
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In the Choose data intermediate window, select the salesforce object. In this article, Contact is selected as that is the object of interest. After selecting the contact object, I can see the preview of the data which matched what exist in the salesforce platform.
Click Create
![5]()
As seen in the screenshot below, we have successfully integrated the data in Dataflow Gen2 in Microsoft Fabric!
![6]()
The next step is to provide the destination target. In this article, we would land the data in Fabric Lakehouse. Therefore, I added Lakehouse as destination and selected the Lakehouse_Sale housed in Demo Fabric workspace as seen below. I also provided salesforce_contact as table name
Then, I selected save, run & close button in the dataflow gen2 to kick-off the ingestion to the Lakehouse
![7]()
In the screenshot below, the data is now ingested into the Lakehouse as seen below!
![8]()
Conclusion
Integrating Salesforce with Microsoft Fabric using Dataflow Gen2 provides a modern, scalable, and low-code approach to bringing CRM data into your enterprise analytics ecosystem. With native Salesforce connectivity, intuitive Power Query transformations, and seamless loading into Fabric Lakehouse or Warehouse, organizations can unlock faster insights and build a unified data platform without complex ETL development.
By leveraging this integration, teams can automate data ingestion, improve data accessibility, and empower business users with real-time dashboards and advanced analytics through Power BI. Whether your goal is sales reporting, customer intelligence, or AI-driven decision-making, Microsoft Fabric and Dataflow Gen2 offer a powerful foundation for transforming Salesforce data into actionable business value.
As cloud data platforms continue to evolve, mastering integrations like this becomes essential for modern data engineers and analytics professionals.