公开(公告)号：US11514007B1

公开(公告)日：2022-11-29

申请号：US17356914

申请日：2021-06-24

Applicant: SAP SE

Inventor： Simon Hoppermann ,  Janick Frasch ,  Andre Sres ,  Masoud Aghadavoodi Jolfaei ,  Mirko Hin ,  Roman Rommel ,  Brian McKellar ,  Steffen Knoeller ,  Santo Bianchino ,  Kuan Lu ,  Dominik Heere

IPC: G06F16/00 ,  G06F16/21 ,  G06F16/245 ,  G06N20/00 ,  G06F16/951 ,  G06F16/25

Abstract: Computer-readable media, methods, and systems are disclosed for storing and analyzing dynamic data within a semantic data store. The dynamic data comprises one or more types of data having a normalized data schema. A dynamic data manager interfaces with the semantic data store to instruct storage of the data. The data may be received through an event service from either of an external data source or an internal data source.

公开(公告)号：US20230091954A1

公开(公告)日：2023-03-23

申请号：US17477807

申请日：2021-09-17

Applicant: SAP SE

Inventor： Roman Rommel ,  Philipp Knuesel ,  Janick Frasch ,  Santo Bianchino

IPC: H04L12/911 ,  H04L29/06 ,  G06F9/48 ,  H04L12/24

Abstract: Computer-readable media, methods, and systems are disclosed for scheduling a start time and a shutdown time of one or more online resources associated with a multi-cloud resource scheduler. A request from a first user is received to access a multi-cloud resource scheduler associated with one or more online resources. Responsive to the request from the first user, credentials of the first user are validated prior to providing access to the multi-cloud resource scheduler. Based upon validating the credentials of the first user, access to the multi-cloud resource scheduler is provided. Instructions are received from the first user to schedule a start time and a shutdown time of at least one online cloud resource connected to the multi-cloud resource scheduler. An availability of the at least one online cloud resource is established for access by a second user based on the instructions.

公开(公告)号：US20210089860A1

公开(公告)日：2021-03-25

申请号：US16659271

申请日：2019-10-21

Applicant: SAP SE

Inventor： Dominik Heere ,  Steffen Knoeller ,  Masoud Aghadavoodi Jolfaei ,  Simon Hoppermann ,  Santo Bianchino ,  Andre Sres ,  Mirko Hin ,  Janick Frasch ,  Kuan Lu ,  Roman Rommel

IPC: G06N3/00 ,  G06N5/04 ,  G06N20/00

Abstract: Techniques for implementing a digital assistant that provides proactive notifications to users, summarizes data and relevant situations, forecasts/predicts future outcomes, simulates outcomes under different assumptions, generates recommendations to improve observed or assumed situations, and provides explanations for calculated outcomes are disclosed. In some example embodiments, a computer system is configured to detect a data change in one or more data sources, the data change corresponding to a monitored data object, generate a predicted future value for the monitored data object based on the detected data change, identify a deviation between the predicted future value and a planned future value for the monitored data object, determine that the identified deviation is relevant for a specific user at a specific time and in a specific context, and cause a notification corresponding to the deviation to be displayed on a computing device based on the determination that the deviation is relevant.

公开(公告)号：US20240297853A1

公开(公告)日：2024-09-05

申请号：US18646316

申请日：2024-04-25

Applicant: SAP SE

Inventor： Roman Rommel ,  Philipp Knuesel ,  Janick Frasch ,  Santo Bianchino

IPC: H04L47/70 ,  G06F9/48 ,  H04L9/40 ,  H04L41/22

CPC classification number: H04L47/827 ,  G06F9/4887 ,  H04L41/22 ,  H04L47/826 ,  H04L63/108

Abstract: Computer-readable media, methods, and systems are disclosed for scheduling a start time and a shutdown time of one or more online resources associated with a multi-cloud resource scheduler. A request from a first user is received to access a multi-cloud resource scheduler associated with one or more online resources. Responsive to the request from the first user, credentials of the first user are validated prior to providing access to the multi-cloud resource scheduler. Based upon validating the credentials of the first user, access to the multi-cloud resource scheduler is provided. Instructions are received from the first user to schedule a start time and a shutdown time of at least one online cloud resource connected to the multi-cloud resource scheduler. An availability of the at least one online cloud resource is established for access by a second user based on the instructions.

公开(公告)号：US12003428B2

公开(公告)日：2024-06-04

申请号：US17477807

申请日：2021-09-17

Applicant: SAP SE

Inventor： Roman Rommel ,  Philipp Knuesel ,  Janick Frasch ,  Santo Bianchino

IPC: H04L47/70 ,  G06F9/48 ,  H04L9/40 ,  H04L41/22

CPC classification number: H04L47/827 ,  G06F9/4887 ,  H04L41/22 ,  H04L47/826 ,  H04L63/108

Abstract: Computer-readable media, methods, and systems are disclosed for scheduling a start time and a shutdown time of one or more online resources associated with a multi-cloud resource scheduler. A request from a first user is received to access a multi-cloud resource scheduler associated with one or more online resources. Responsive to the request from the first user, credentials of the first user are validated prior to providing access to the multi-cloud resource scheduler. Based upon validating the credentials of the first user, access to the multi-cloud resource scheduler is provided. Instructions are received from the first user to schedule a start time and a shutdown time of at least one online cloud resource connected to the multi-cloud resource scheduler. An availability of the at least one online cloud resource is established for access by a second user based on the instructions.

公开(公告)号：US20220405651A1

公开(公告)日：2022-12-22

申请号：US17835506

申请日：2022-06-08

Applicant: SAP SE

Inventor： Philipp Knuesel ,  Andre Sres ,  Mirko Hin ,  Roman Rommel ,  Janick Frasch ,  Santo Bianchino ,  Dominik Heere

IPC: G06N20/20 ,  H04L67/10

Abstract: Some embodiments are directed to a federated machine learning, including the inference and training. Inference may be done by applying multiple machine learnable models to a mapped record. The mapped record may be obtained by applying a mapping rule to a local record. The mapping rule may generalize or extend data features in the local record.