Hello Everyone,
I have created a web application with Python that trains a model and generates predictions and returns the predicted values in json format.
It's not necessary the context of what is predicted, because it's only a proof of concept so I just used simple open dataset of house prices to train and test and LinearRegression model.
Now, I want to integrate that into Qlik Sense, and each time the user interacts with the Seet, we need to get new predictions taken the values selected on the sheet.
I have done half of this exercice and gotten the data from the API into a dimension inside of Qlik Sense and actually displayed the data in a simple table. You can find the details with screenshots in the attached pdf document.
Now the problem is how to actually automate the API Call and data retrieval/update inside Qlik. The dialog between Qlik Sense the server is the most important next step. The final result is to have a Qlik Sense Application that displays KPIs, Charts and all the historical Insights, and Also in a sheet we display predicted values of something that is important to the client (ROI, Prices, Churn of Customer) So we need to send to the server some data element that is selected on the sheet like for example the ID of a customer, the Server gets that ID and predict if that customer will no more do business with us or not, using a pre-trained model, deployed on the server.
Best Regards,
Mohamed Jelidi
