Microsoft Power BI and MongoDB Integration

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Microsoft Power BI + MongoDB integration

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Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Microsoft Power BI and MongoDB

Create a New Scenario to Connect Microsoft Power BI and MongoDB

In the workspace, click the β€œCreate New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Microsoft Power BI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Microsoft Power BI or MongoDB will be your first step. To do this, click "Choose an app," find Microsoft Power BI or MongoDB, and select the appropriate trigger to start the scenario.

Add the Microsoft Power BI Node

Select the Microsoft Power BI node from the app selection panel on the right.

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Configure the Microsoft Power BI

Click on the Microsoft Power BI node to configure it. You can modify the Microsoft Power BI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the MongoDB Node

Next, click the plus (+) icon on the Microsoft Power BI node, select MongoDB from the list of available apps, and choose the action you need from the list of nodes within MongoDB.

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Authenticate MongoDB

Now, click the MongoDB node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your MongoDB settings. Authentication allows you to use MongoDB through Latenode.

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Configure the Microsoft Power BI and MongoDB Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the Microsoft Power BI and MongoDB Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Microsoft Power BI, MongoDB, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking β€œRun once” and triggering an event to check if the Microsoft Power BI and MongoDB integration works as expected. Depending on your setup, data should flow between Microsoft Power BI and MongoDB (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Microsoft Power BI and MongoDB

Microsoft Power BI + Google Sheets: When a Microsoft Power BI report is updated, its data is retrieved and a new row is added to a Google Sheet for wider team access and analysis.

MongoDB + Microsoft Power BI + Slack: When a document is updated in MongoDB, a search is performed to find related documents. If changes impact a Power BI dataset, a notification is sent to data analysts in a Slack channel.

Microsoft Power BI and MongoDB integration alternatives

About Microsoft Power BI

Use Power BI in Latenode to automate report generation and data analysis. Trigger report refreshes based on real-time events, then use Latenode to share insights across your team via Slack, email, or other apps. Automate your analytics pipeline and react faster, without manual Power BI updates. Latenode adds scheduling and distribution.

About MongoDB

Use MongoDB in Latenode to automate data storage and retrieval. Aggregate data from multiple sources, then store it in MongoDB for analysis or reporting. Latenode lets you trigger workflows based on MongoDB changes, create real-time dashboards, and build custom integrations. Low-code tools and JavaScript nodes unlock flexibility for complex data tasks.

See how Latenode works

FAQ Microsoft Power BI and MongoDB

How can I connect my Microsoft Power BI account to MongoDB using Latenode?

To connect your Microsoft Power BI account to MongoDB on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Microsoft Power BI and click on "Connect".
  • Authenticate your Microsoft Power BI and MongoDB accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I visualize MongoDB data in Power BI automatically?

Yes, you can! Latenode automates data transfers from MongoDB to Power BI. Gain real-time insights by visualizing MongoDB data directly in Power BI dashboards, automatically keeping you informed.

What types of tasks can I perform by integrating Microsoft Power BI with MongoDB?

Integrating Microsoft Power BI with MongoDB allows you to perform various tasks, including:

  • Create live dashboards from MongoDB real-time data.
  • Generate reports on sales trends stored in MongoDB.
  • Track website user behavior using Power BI dashboards.
  • Automate monthly reporting with scheduled workflows.
  • Visualize product performance from MongoDB databases.

How does Latenode handle large datasets from MongoDB to Microsoft Power BI?

Latenode's architecture efficiently handles large datasets, using optimized data transfer and processing, ensuring scalable reporting in Power BI without performance bottlenecks.

Are there any limitations to the Microsoft Power BI and MongoDB integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Complex data transformations may require custom JavaScript code.
  • Initial data synchronization can take time for very large datasets.
  • Microsoft Power BI API request limits apply to real-time updates.

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