Machine Learning Cockpit for SAP Business ByDesign
Do you think there is a use for Machine Learning in Small and Medium Enterprises?
Would you like to be able to design predictive scenarios on your own directly in SAP Business ByDesign? At no extra cost, no external service to use, no developer or data scientist required?
If you have this ambitions then this blog is for you.
In SAP Business ByDesign release 2211 we are introducing Machine Learning Cockip.
Machine Learning Cockpit for SAP Business ByDesign is SAP implementation of standard machine learning workflow within SAP Business ByDesign user interface.
Machine Learning Cockpit (MLC) brings Predictive Analytics capabilities to Business ByDesign by utilizing the power of Predictive Analytical Library (PAL) of SAP HANA of Business ByDesign tenant.
The tool allows users to create predictive scenarios by using data of Business Analytics data sources, on which PAL machine learning algorithms try to learn the model in the training process. This model can be applied to new data to make actual predictions. The predictions can be then consumed directly in the Business ByDesign business documents, in Business Analytics, or in PDI solutions (through provided API).
Machine Learning Cockpit (MLC) is relevant to partners who want to provide their customers intelligent solutions that are based on analytical predictions.
Machine Learning Cockpit (MLC) implements standard ML workflow directly in Business ByDesign user interface. Users are guided through the ML workflow in an easy-to-use interface. Thus, users can focus on the business context of their predictive scenarios and do not have to deal with the complexity of Predictive Analytical Library (PAL).
The MLC is a fully embedded solution. All the data used in the pre-processing, model training and predictions never leave Business ByDesign tenant.
- For more information about Machine Learning Cockip please refer to Online Help: Overview of Machine Learning Cockpit
- In this blog my colleague Sergio Fernandez shares experience with his restaurant visit on the day when they were not able to serve his favouring food. And he provides solution! Machine Learning and the Restaurant without Paella
Stay tuned. More blogs, videos and tutorial to be followed.
Hello dalibor , I hope you are well.
I understand that there are 3 ways to consume the prediction results, through the use of the data source, use of the integrated component and through the use in extension fields, how could we use it concretely in a field? I have made tests however I can not select any field created in the prediction execution, is there any other step or additional process to consider to be able to reflect the result in a field?
As general rule, extension fields must be created in the same business object/ business context as is the datasource anchor. If you did it this way then you have maybe stumbled upon some technical issue which we would love to resolve asap.
Can you be please share details regarding what dat source you used and where exactly did you create extension fields?