公开(公告)号：US11972312B2

公开(公告)日：2024-04-30

申请号：US17834329

申请日：2022-06-07

Applicant: SAP SE

Inventor： Mohit V Gadkari ,  Anirudh Prasad ,  Pankaj Kumar Agrawal ,  Yatish Nagaraja ,  Kopal Jauhari ,  Namrata ,  Jovin Jijo

IPC: G06F9/44 ,  G06F9/54 ,  G06F16/23 ,  G06F16/27 ,  G06F9/448

CPC classification number: G06F9/548 ,  G06F9/541 ,  G06F16/235 ,  G06F16/275 ,  G06F9/4488

Abstract: Disclosed herein are system, method, and computer program product embodiments for synchronizing data in a source system to an application without relying on middleware. An embodiment operates by performing an initial load of records for an object for an application from a source system, thereby retrieving a first set of records. The embodiment first maps the first set of records to the object using a transform template. The embodiment creates the object in the application using the first set of records based on the first mapping. The embodiment performs a delta load of records for the object from the source system, thereby retrieving a second set of records. The embodiment second maps the second set of records to the object using the transform template. The embodiment then updates the object using the second set of records based on the second mapping.

公开(公告)号：US20240104424A1

公开(公告)日：2024-03-28

申请号：US17952107

申请日：2022-09-23

Applicant: SAP SE

Inventor： Mohit V. Gadkari ,  Ankur Malik ,  Sunil S. Parvatikar ,  Simona Marincei ,  Dalibor Knis ,  Anirudh Prasad ,  Kopal Jauhari ,  Saurabh Saxena ,  Yatish Nagaraja ,  Pankaj Kumar Agrawal ,  Long Qian ,  Varun Verma

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: The present disclosure involves systems, software, and computer implemented methods for an artificial intelligence work center for ERP data. One example method includes receiving scenario and model settings for an artificial intelligence model for a predictive scenario. A copy of the dataset is processed based on settings to generate a prepared dataset that is provided with the settings to a predictive analytical library. A trained model trained and evaluation data for the trained model is received from the predictive analytical library. A request is received to generate a prediction for the predictive scenario for a target field for a record of the dataset. The record of the dataset is provided to the trained model and a prediction for the target field for the record the dataset is received from the model. The prediction is included for presentation in a user interface that displays information from the dataset.