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Data sources

Power BI integrations for the systems your business runs on

Power BI integrations are the connections that bring data from business systems, such as a CRM, an ERP or a database, into one reporting model. Some sources have a connector from Microsoft, while others need an API, an export or a staging database. The pages below explain the honest route for each system, so you know the effort before work begins.

  • Connector or API route
  • Refresh planned early
  • Honest about limits

Last updated

How do Power BI integrations work?

Every report begins with a connection. Power Query reaches into a source, reads the tables and shapes them. After that, the data lands in a semantic model where measures live.

There are two main ways to hold the data. Import copies it into the model on a schedule, so reports respond quickly. DirectQuery leaves the data in the source and asks for it live instead. Each choice has trade-offs, and the right one depends on volume and freshness.

Sources inside a private network also need a gateway. It is a small service on a machine in your network that passes queries through safely. Therefore we plan the gateway early, because it often involves your IT team.

Yellow network cables with clear connectors, illustrating Power BI Integrations

Browse every Power BI integration

Payroll and HR data

ADP

Web analytics reporting

Adobe Analytics

Airtable reporting

Airtable

Athena reporting

Amazon Athena

Redshift warehouse

Amazon Redshift

S3 bucket data

Amazon S3

Work management data

Asana

Azure Analysis Services reporting

Azure Analysis Services

Azure Blob Storage reporting

Azure Blob Storage

Azure Cosmos DB reporting

Azure Cosmos DB

Azure Data Explorer reporting

Azure Data Explorer

Pipelines and refresh

Azure Data Factory

Data lake reporting

Azure Data Lake

Azure DevOps reporting

Azure DevOps

Azure SQL source

Azure SQL Database

Azure Synapse reporting

Azure Synapse

Business Central reporting

Business Central

Databricks and Power BI

Databricks

Dataverse reporting

Dataverse

Dynamics 365 reporting

Dynamics 365

Excel and Power BI

Excel

Fabric Lakehouse reporting

Fabric Lakehouse

Paid social reporting

Facebook Ads

Engineering data

GitHub

Ad spend reporting

Google Ads

Web analytics in Power BI

Google Analytics

BigQuery and Power BI

Google BigQuery

Google Sheets source

Google Sheets

HubSpot and Power BI

HubSpot

IBM Db2 reporting

IBM Db2

JSON data sources

JSON

Jira delivery reporting

Jira

Email marketing data

Mailchimp

MariaDB reporting

MariaDB

Microsoft Access reporting

Microsoft Access

Survey reporting

Microsoft Forms

Reports where people talk

Microsoft Teams

Document data

MongoDB

MySQL reporting

MySQL

NetSuite reporting

NetSuite

ODBC data sources

ODBC

OData feeds

OData

OneDrive reporting

OneDrive

Oracle and Power BI

Oracle

PDF data sources

PDF

PostgreSQL and Power BI

PostgreSQL

Reports that act

Power Apps

Reports that start actions

Power Automate

Python in reports

Python

QuickBooks reporting

QuickBooks

APIs in both directions

REST API

SAP and Power BI

SAP

SAP BW reporting

SAP BW

SAP HANA reporting

SAP HANA

SQL Server and Power BI

SQL Server

SSAS reporting

SQL Server Analysis Services

Finance reporting

Sage Intacct

Salesforce and Power BI

Salesforce

ServiceNow reporting

ServiceNow

SharePoint and Power BI

SharePoint

Shopify store reporting

Shopify

Smartsheet reporting

Smartsheet

Snowflake and Power BI

Snowflake

Payments and revenue

Stripe

Teradata reporting

Teradata

Trello board reporting

Trello

Store reporting

WooCommerce

HR and people data

Workday

Small business finance

Xero

Support analytics

Zendesk

Sales pipeline data

Zoho CRM

Board data reporting

monday.com

Types of Power BI integrations we set up

Most source systems fall into one of six groups, and each group brings its own questions.

CRM systems

Accounts, deals and activities feed sales dashboards, so field mapping and custom objects need care.

ERP and finance

Ledgers, invoices and stock records drive finance reports, and they often hide logic inside the application.

Databases and warehouses

SQL sources connect directly, and query folding keeps refresh fast when the model is set up well.

Files and SharePoint

Excel workbooks and lists still hold key data, so we give them a stable folder and a fixed layout.

Marketing and web data

Web analytics and campaign tools show demand, but sampling and API limits can shape what is possible.

Microsoft 365 tools

Teams, Power Automate and other tools carry reports to people and trigger actions from the numbers.

Why do some data source connections fail?

A connection that works on day one can still break later. Usually the cause is simple. A password expires, a column gets a new name, or an API changes its limits. So a good setup expects change and reports it clearly.

Volume is the second cause. A query that reads every row each night grows slower each month. Incremental refresh solves this, because it loads only the new and changed rows. However, it needs a reliable date column in the source.

The third cause is ownership. When nobody owns the refresh, failures go unseen for days. We therefore name an owner on your side and set up failure alerts before handover.

What to check before you connect a source

These six questions save time, and we ask them on the first call.

  • Does Microsoft list a connector for this system
  • Is the data in the cloud or on a private network
  • Who can grant a service account with read access
  • How fresh must the numbers be each day
  • How many rows does the largest table hold
  • Which fields are sensitive and need access rules

How we build Power BI integrations

The work runs in four stages, and each one ends with your sign-off.

  1. Confirm the route

    First we check the Microsoft connector list and the vendor documentation, then we tell you plainly which route fits.

  2. Arrange access

    Next your IT team creates a read-only account, so the work happens inside your own tenant with least privilege.

  3. Model the data

    We shape the tables into a star schema and define each measure once, because reports depend on that base.

  4. Set refresh and alerts

    Finally we schedule refresh, test a failure and hand over notes, so your team can run it alone.

Questions about Power BI integrations

Which Power BI integrations have a native connector?

Microsoft publishes the current connector list in its Power Query documentation, and it changes over time. Therefore we check that list for every project instead of relying on memory. Each page in this section states whether a connector exists for that system. Where none exists, the page describes the alternative route honestly.

Can Power BI integrations combine several systems in one report?

Yes. Combining sources is one of the main strengths of the tool. For example, a model can join CRM deals to ERP invoices through a shared customer key. However, the keys must match, so we often build a small mapping table first. After that, one report can show the full picture.

Do Power BI integrations need a gateway?

Only when the source sits on a private network, such as a SQL Server in your own data center. Cloud sources usually connect without one. When a gateway is needed, we help your IT team install it on a machine that stays on. We also document which sources use it.

What if a system has no connector at all?

There is almost always a route. Many applications offer an API, an ODBC driver or a scheduled export. Otherwise a staging database can collect the data first. We explain the effort and the limits of each option before you commit, so the choice is yours and it is an informed one.

Is our data copied outside our tenant?

No. The work happens inside your own Microsoft tenant, and we use accounts that you create and control. Import mode does copy data into your semantic model, but that model also sits in your tenant. As a result, nothing leaves your environment, and you can remove our access at any time.

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