DataRobot analytics source
DataRobot is a machine-learning platform for automating, assuring, and accelerating predictive analytics, helping data scientists and analysts to build and deploy accurate predictive models.
To connect to DataRobot, you must have created, or have access to, a model and deployed it to an endpoint on the DataRobot platform. This endpoint must be publicly accessible by Qlik Cloud.
DataRobot has endpoints quotas:
The resources available on the DataRobot services where the model has been deployed will impact and limit performance in the Qlik Sense reload and chart responsiveness.
The DataRobot connector is limited to 200k (100K for DataRobot Timeseries) rows per request. These are sent to the endpoint service in batches of 2k rows. In scenarios where more rows are required to be processed, use a Loop within the Data load script to process more rows in batches.
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 DataRobot endpoint.
When using DataRobot connections in a chart expression it is recommended to provide the datatypes of the fields as the model needs to process these in the correct string/numeric format. A limitation of server side extensions in chart expressions is that the data types are not automatically detected as they are in the load script.
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.