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Use the CData ODBC Driver for MongoDB to visualize MongoDB data in Power BI Desktop.
With built-in support for ODBC on Microsoft Windows, the CData ODBC Drivers provide self-service integration with self-service analytics tools such as Microsoft Power BI. The CData ODBC Driver for MongoDB links your Power BI reports to operational MongoDB data. You can monitor MongoDB data through dashboards and ensure that your analysis reflects MongoDB data in real time by scheduling refreshes or refreshing on demand. This article details how to use the ODBC driver to create real-time visualizations of MongoDB data in Microsoft Power BI Desktop and then upload to Power BI.
The CData ODBC Drivers offer unmatched performance for interacting with live MongoDB data in Power BI due to optimized data processing built into the driver. When you issue complex SQL queries from Power BI to MongoDB, the driver pushes supported SQL operations, like filters and aggregations, directly to MongoDB and utilizes the embedded SQL Engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze MongoDB data using native Power BI data types.
About MongoDB Data Integration
Accessing and integrating live data from MongoDB has never been easier with CData. Customers rely on CData connectivity to:
- Access data from MongoDB 2.6 and above, ensuring broad usability across various MongoDB versions.
- Easily manage unstructured data thanks to flexible NoSQL (learn more here: Leading-Edge Drivers for NoSQL Integration).
- Leverage feature advantages over other NoSQL drivers and realize functional benefits when working with MongoDB data (learn more here: A Feature Comparison of Drivers for NoSQL).
MongoDB's flexibility means that it can be used as a transactional, operational, or analytical database. That means CData customers use our solutions to integrate their business data with MongoDB or integrate their MongoDB data with their data warehouse (or both). Customers also leverage our live connectivity options to analyze and report on MongoDB directly from their preferred tools, like Power BI and Tableau.
For more details on MongoDB use case and how CData enhances your MongoDB experience, check out our blog post: The Top 10 Real-World MongoDB Use Cases You Should Know in 2024.
Getting Started
Connect to MongoDB as an ODBC Data Source
If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.
Set the Server, Database, User, and Password connection properties to connect to MongoDB. To access MongoDB collections as tables you can use automatic schema discovery or write your own schema definitions. Schemas are defined in .rsd files, which have a simple format. You can also execute free-form queries that are not tied to the schema.
Create Data Visualizations
After creating an ODBC DSN, follow the steps below to connect to the MongoDB ODBC DSN from Power BI Desktop:
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Open Power BI Desktop and click Get Data -> More... to open the Get Data window.
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In the Get Data window select Other -> ODBC to open the next window.
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Select the DSN in the menu. If you know the SQL query you want to use to import data, you can expand the Advanced options node and enter the query in the SQL Statement box. Otherwise, click OK to continue.
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Choose Default or Custom as the authentication option and click Connect.
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Select tables in the Navigator dialog.
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Click Transform Data to edit the query. The table you imported is displayed in the Power Query Editor. In the Power Query Editor, you can enrich your local copy of MongoDB data with other data sources, pivot MongoDB columns, and more. Power BI detects each column's data type from the MongoDB metadata retrieved by the driver.
Power BI records your modifications to the query in the Applied Steps section, adjusting the underlying data retrieval query that is executed to the remote MongoDB data. When you click Close and Apply, Power BI executes the data retrieval query.
Otherwise, click Load to pull the data into Power BI.
Create Data Visualizations
After pulling the data into Power BI, you can create data visualizations in the Report view by dragging fields from the Fields pane onto the canvas. Follow the steps below to create a pie chart (Salesforce shown):
- Select the pie chart icon in the Visualizations pane.
- Select a dimension in the Fields pane: for example, Name.
- Select a measure in the Fields pane: for example, Annual Revenue.
You can change sort options by clicking the ellipsis (...) button for the chart. Options to select the sort column and change the sort order are displayed.
You can use both highlighting and filtering to focus on data. Filtering removes unfocused data from visualizations; highlighting dims unfocused data. You can highlight fields by clicking them:
You can apply filters at the page level, at the report level, or to a single visualization by dragging fields onto the Filters pane. To filter on the field's value, select one of the values that are displayed in the Filters pane.
Click Refresh to synchronize your report with any changes to the data.
Free Trial & More Information
If you are interested in connecting to your MongoDB data from Microsoft Power BI, or any applications that support ODBC connectivity, download a free, 30-day trial of the CData ODBC Driver for MongoDB. As always, our world-class support team is ready to answer any questions you may have.