Early Access: The content on this website is provided for informational purposes only in connection with pre-General Availability Qlik Products.
All content is subject to change and is provided without warranty.
Skip to main content Skip to complementary content

Azure OpenAI analytics source

Use the Azure OpenAI analytics connector to communicate with Microsoft's Azure OpenAI service, available within Azure's Cognitive Services. With this connector, you can enrich your Qlik Sense apps with contextual and analytical depth from generative AI models, such as those which power ChatGPT.

With the Azure OpenAI analytics connector, you can send data from your app's data model to the Azure OpenAI service. You can connect to this analytics source from the Create page of the Analytics activity center or within an app.

What is Azure OpenAI Service?

Enabling ML endpoints in Qlik Cloud

To work with this connector, machine learning endpoints must be enabled in the Administration activity center. The switch is located under Feature control in the Settings section. Use the swithc.

For more information, see Enabling analytic connections for machine learning endpoints.

Limitations

  • The APIs accessed through this connector enforce an endpoint quota and rate limiting, which are subject to the individual terms of your Microsoft Azure services.

  • Usage of the Azure OpenAI analytics connector will impact and limit performance in the Qlik Sense reload and chart responsiveness. The degree to which this performance is affected depends on your use case.

  • The different configurations of this connector send data to the endpoint service with the following limits:

    • OpenAI Completions API - Rows: Request limit of 25 rows per request, with a maximum batch size of 20 rows being sent at a time.

    • OpenAI Chat Completions API - Rows: Request limit of 25 rows per request, with a maximum batch size of one row being sent at a time.

  • In a scenario where an application is regularly reloaded, it is best practice to cache the predictions using a QVD file and only send the new rows to the prediction endpoint. This will improve the performance of the Qlik Sense application reload and reduce the load on the endpoint.

  • If you are using a relative connection name, and if you decide to move you app from a shared space to another shared space, or if you move your app from a shared space to your private space, then it will take some time for the analytic connection to be updated to reflect the new space location.

Did this page help you?

If you find any issues with this page or its content – a typo, a missing step, or a technical error – let us know how we can improve!