How to: Getting started with the Qlik AutoML connector in Qlik Application Automation
This article provides an overview of getting started with the Qlik AutoML connector in Qlik Application Automation.
The Qlik AutoML connector in Qlik Application Automation is created to enable users to obtain predictions generated by the Qlik AutoML using automations.
Using the connector
The connector has two blocks available:
Generate Realtime Prediction Result: This block creates a prediction for the provided input based on a model in Qlik AutoML.
Generate Multiple Realtime Prediction Results: This block creates a prediction for the provided input based on a model in Qlik AutoML. It block accepts a maximum of 10.000 rows or 100.000 cells.
After you have run the experiments on Qlik AutoML and deployed the models, you can use the Qlik Application Automation to get Realtime Prediction results on the go.
Lets go with a Lead Qualification example where we update the Lead Conversion Probability in a CRM system based on the new information obtained about a lead, running the new information against the trained model and updating the probability in the system. This can help the Marketing Team focus their efforts towards a more probable lead.
Open a blank automation and search for Lead incremental block under the SugarCRM connector and drag it on to the canvas and place it under the start block. This will fetch us the new and updated leads from the CRM.
Drag a Filter List block from under the Lists blocks to filter the list of leads so they only contain the newly added data.
Drag the Generate Realtime Prediction Result and place it inside the Filter List loop.
When you 'do lookup' under the deployment ID, you will be able to see all the deployments you have in your tenant. Select the Lead Qualification deployment.
When providing the features, you provide column names that are the same as in the training data set and provide values for each of those keys from the lead object you got in the filter list.
Add an Update Lead block from the SugarCRM connector under the AutoML block and map the result from the Prediction to the field you want to update. Add another custom field to satisfy the filter list block condition we added.
When you run the automation, you will be able to get the prediction result for the features you provided from the new lead and the prediction result will be updated in the CRM system.
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.