Sap Se

Sap Ag

Manikanta Pachineelam

Yingjiong He

Yufeng Zhou

Usha Hanumolu

Sivakumar Nagapandi

Tu Truong

Sivakumar N

Nethaji Tummuru

Jaehun Jeong

Mario Ponce

Sakshi Chopra

Zhenhua Luo

Nalini Chandhi

Chao Zhou

Rahul Kabra

Systems, methods, and apparatuses for activity pattern detection are described herein. Embodiments may process large amounts of data from a plurality of different database sources in order to detect events common to the data of the different database sources. Embodiments further perform data mining operations to detect patterns (e.g., two or more events appearing consecutively or non-consecutively), and present these patterns in a graphical user interface (GUI) to illustrate how a plurality of patterns may comprise a business scenario.

Systems, methods, and apparatuses for detecting activity patterns

A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a sales territory business object.

Consistent interface for sales territory message type set 2

Consistent interface for sales territory message type set 1

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Mountain View, CA, United States of America

Manikanta Pachineelam