SAP had 37 patents in big data during Q2 2024. The patents filed by SAP SE in Q2 2024 focus on various aspects of data analysis and integration. One patent involves identifying data patterns based on time series data and selecting predictive models based on deviation risks. Another patent relates to training a machine learning model to predict transit times for improved planning. A third patent addresses compensating for environmental impact in a network or datacenter by calculating energy consumption and providing compensation suggestions. The last patent involves integrating data privacy protocols across system landscapes by coordinating communication between different applications and tenants within the system. GlobalData’s report on SAP gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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SAP had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: Time series prediction execution based on deviation risk evaluation (Patent ID: US20240202579A1)
The patent filed by SAP SE describes a computer-implemented method for identifying data patterns based on time series data observations. The method involves performing a cross-validation assessment of predictive models, determining deviation risks for each model, excluding models based on these risks, and selecting a candidate model based on accuracy evaluation. The selected model is then used for predicting values for a future horizon, with the process being automated for service process execution.
The system outlined in the patent involves one or more processors and computer-readable memories executing operations to perform the method described. It includes obtaining time series data, generating predictive models for predicting measure variables, and selecting models such as double exponential smoothing, auto regression, linear regression, or exponential smoothing models. The system also executes the selected candidate model to provide predicted values for the requested time horizon, which can be used for automation of service process execution. The comparison of forecasting variability distribution is done based on a deviation rejection rule to exclude models with deviations above a certain threshold, ensuring the accuracy and reliability of the predictive models.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
