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The Microsoft Teams ODBC Driver is a powerful tool that allows you to connect with live data from Microsoft Teams, directly from any applications that support ODBC connectivity.

Access Microsoft Teams data like you would a database - read, write, and update Microsoft Teams Groups, Teams, Channels, Messages, etc. through a standard ODBC Driver interface.

Connect to and Query Microsoft Teams Data in QlikView over ODBC



Create data visualizations with Microsoft Teams data in QlikView.

The CData ODBC drivers expand your ability to work with data from more than 200 data sources. QlikView is a business discovery platform that provides self-service BI for all business users in an organization. This article outlines simple steps to connect to Microsoft Teams data using the CData ODBC driver and create data visualizations in QlikView.

The CData ODBC drivers offer unmatched performance for interacting with live Microsoft Teams data in QlikView due to optimized data processing built into the driver. When you issue complex SQL queries from QlikView to Microsoft Teams, the driver pushes supported SQL operations, like filters and aggregations, directly to Microsoft Teams 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 Microsoft Teams data using native QlikView data types.

Connect to Microsoft Teams 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.

You can connect to MS Teams using the embedded OAuth connectivity. When you connect, the MS Teams OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Populate a Chart with Microsoft Teams Data

The steps below supply the results of an SQL query to a visualization in QlikView. In this article, you will create a bar chart with the query below:

SELECT subject, location_displayName FROM Teams WHERE Id = 'Jq74mCczmFXk1tC10GB'
  1. Click File -> Edit Script (or click the Edit Script button in the Toolbar).
  2. On the Data tab, select ODBC in the Database menu and click Connect.
  3. Select the DSN (CData MSTeams Sys) in the resulting dialog. A command like the following is generated: ODBC CONNECT TO [CData MSTeams Sys];
  4. Enter the SQL query directly into the script with the SQL command (or click Select to build the query in the SELECT statement wizard). SQL SELECT subject, location_displayName FROM Teams WHERE Id = 'Jq74mCczmFXk1tC10GB';

    Where possible, the SQL operations in the query, like filters and aggregations, will be pushed down to Microsoft Teams, while any unsupported operations (which can include SQL functions and JOIN operations) will be managed client-side by the CData SQL engine embedded in the driver.

  5. Close the script editor and reload the document to execute the script.
  6. Click Tools -> Quick Chart Wizard. In the wizard, select the chart type. This example uses a bar chart. When building the chart, you have access to the fields from Microsoft Teams, typed appropriately for QlikView, thanks to built-in dynamic metadata querying.
  7. When defining Dimensions, select subject in the First Dimension menu.
  8. When defining Expressions, click the summary function you want and select location_displayName in the menu.
  9. Finish the wizard to generate the chart. The CData ODBC Driver for Microsoft Teams connects to live Microsoft Teams data, so the chart can be refreshed to see real-time changes. Live connections are possible and effective, thanks to the high-performance data processing native to CData ODBC Drivers.