Connect to and Query Strava Data in QlikView over ODBC

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Create data visualizations with Strava data in QlikView.

The CData ODBC drivers expand your ability to work with data from hundreds of 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 Strava data using the CData ODBC driver and create data visualizations in QlikView.

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

Connect to Strava 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.

To authenticate to Strava, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.

Using OAuth Authentication

You must create a custom OAuth application to connect to Strava. To create a custom OAuth application:

  1. Log into the Strava API Settings page
  2. Create a new application or select an existing application
  3. Set the "Authorization Callback Domain" to your callback URL domain (e.g. localhost)
  4. Note down the Client ID and Client Secret

After setting the following connection properties, you are ready to connect:

  • AuthScheme: Set this to OAuth.
  • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
  • OAuthClientId: Set this to the Client ID from your Strava API application.
  • OAuthClientSecret: Set this to the Client Secret from your Strava API application.
  • CallbackURL: Set this to the redirect URI matching your application's callback domain.

Example connection string:

Profile=C:\profiles\Strava.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=http://localhost:33333;

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 Strava 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 ,  FROM Athlete WHERE  = ''
  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 API Sys) in the resulting dialog. A command like the following is generated:
    ODBC CONNECT TO [CData API 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 ,  FROM Athlete WHERE  = '';
    

    Where possible, the SQL operations in the query, like filters and aggregations, will be pushed down to Strava, 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 Strava, typed appropriately for QlikView, thanks to built-in dynamic metadata querying.
  7. When defining Dimensions, select in the First Dimension menu.
  8. When defining Expressions, click the summary function you want and select in the menu.
  9. Finish the wizard to generate the chart. The CData ODBC Driver for Strava connects to live Strava 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.

Ready to get started?

Connect to live data from Strava with the API Driver

Connect to Strava