Data Attribute Recommendation

Perform classification and regression tasks with this machine learning-based service available on SAP Business Technology Platform.

Getting Started

First Steps

Data Attribute Recommendation is part of the SAP AI Services portfolio and available on SAP Business Technology Platform (SAP BTP).

It uses free text, numbers and categories as input to classify entities such as products, stores and users into multiple classes and also to predict the value of missing numerical attributes in your data records.

With Data Attribute Recommendation, companies can:

  • Use classification and regression capabilities to speed up data management processes
  • Reduce errors and manual efforts for completing business processes
  • Increase data consistency and accuracy

Get started

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Key Features

Data flexibility
Be flexible in uploading and storing data in separate datasets.

Model training metrics
Expose model training metrics after a successful training run.

Model templating
Pick one of multiple machine learning models that best suits your needs.

AutoML model template
Choose the best fitting machine learning pipeline for single label classification tasks.

Deployment flexibility
Deploy multiple models at the same time while having the flexibility to configure the inference response.

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From Chaos to Clarity: Boost Your Business Data with SAP AI Services

Discover how to maximize the potential of structured business data with SAP AI Services, such as Data Attribute Recommendation and Personalized Recommendation. And see firsthand how the Document Information Extraction service can revolutionize the handling of unstructured data right from the core input channels. The services act as a universal gateway, efficiently selecting and initiating relevant processes and integrating extracted results with structured data.

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Deploy Data Attribute Recommendation Capabilities

Users can easily deploy Data Attribute Recommendation in several business scenarios and extend their own processes.

Classify data records
Classify entities such as products, stores and users into multiple classes, using categorical, numerical and textual inputs.
Implement this use case
Follow the tutorial

Perform a regression on the data to predict a numerical label
Upload a dataset to your Data Attribute Recommendation service instance to afterwards be able to train your machine learning model using the regression model template.
Follow the tutorial

Sales order completion
A business blueprint with dedicated preprocessing for autocompletion of sales orders. The underlying machine learning model can predict custom, defined incompletion log fields, provide custom metrics, and provide a training pipeline enabling the user to define which data should be used for training, testing, and validation to overcome issues with imbalanced data sets.
Start the tutorial