Oracle International Corporation

Ramchand Raman

Ashish Pathak

Usha Arora

Swathi Uppala

Gopal Raja Ratnam

Sreeram Hariharan

Bryan Siu Him So

Keshava Rangarajan

Nagaraj Srinivasan

Chandra Yeleshwarapu

Rixin Zhu

Athanasios Bismpigiannis

Sudeep Agarwal

Sangeetha Mani

Mohammed Hussain Shirkol

Ganga Mohan Nookala

Lalit Agrawal

Alosh Bennet

Kashif Suleman

Krishna Jonnalagadda

Anup Kumar Jha

Fan Yang

Pushkala Nagasuri

Ivan Canales Pineda

Feature engineering can be performed on time series data making the data easy to manipulate and accessible to business users for analysis according to existing best practices. A computer system can, after receiving time series data related to a device, contextualize the time series data based on business data related to the device from, for example, an enterprise resource planning database. The contextualized data can be windowed by a selected feature based on execution data related to the device from, for example, a manufacturing execution system database. The windowed data can be transformed into summary data using a time series transformation. The summary data can be easily manipulated by, for example, generating genetic maps of the segmented and transformed data for clustering or searching for anomalies and patterns in response to user requests or automatically.

Sensor time series data: functional segmentation for effective machine learning

Systems, methods, and computer-readable mediums are presented that may provide for an interface to a relational database. A request may be received for data stored in a relationship database, wherein the request is received from a spreadsheet application. In response to the request for data stored in the relational database, a plurality of tables in the relational database may be accessed to retrieve the data indicated in the request. The retrieved data may be translated from the plurality of tables of the relational database into a format for output to the spreadsheet application. The translated data may be output to the spreadsheet application.

Interfacing with a relational database for multi-dimensional analysis via a spreadsheet application

Changes in the supply chain of one product may affect the price and availability of many other products. Likewise, a product may be composed of a number of smaller parts. Changes in the cost or availability of any of the parts that comprise a product may result in changes in cost or availability of the product as well as many other related products. A supply chain analysis engine is used to model a supply chain. The supply chain analysis engine may identify dependencies between products, sub products, and supply chains. The dependencies may be used to analyze the impact of a change in the supply chain on all relevant products.

Cost impact simulator and gross profit analyzer

According to an embodiment, the present invention provides a method for providing automated decision in response to one or more responses. The method includes providing, at a computer system, a user interface for receiving input from a user. The method also includes detecting a first event. The method further includes receiving a first set of attributes associated with the first event. Also, the method includes processing the first set of attributes. The method additionally includes analyzing the first set of attributes using at least pattern recognition. The method includes determining a first context for the first event based at least on the first set of attributes.

Method and system for providing decision making based on sense and respond

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Redwood City, CA, United States of America

Ramchand Raman