Dilip R Patel

US Patent:

7818661, Oct 19, 2010

Filed:

Oct 4, 2006

Appl. No.:

12/157616

Inventors:

Dilip Patel - Edison NJ, US

International Classification:

G06F 17/27

US Classification:

715212, 715217

Abstract:

For applications of web-based analytics and business intelligence reporting, methods and systems are provided for exporting a data table as a spreadsheet pivot table by automatic creation of formatted spreadsheet pivot tables with application specific initial views. The views are specified by templates allowing a user to view multiple pivot tables in a single spreadsheet book. Pivot tables are created by a remote server that performs the exporting of the data table so that a user can save the pre created pivot table in his/her local machine. In one embodiment of the invention, the data table on which a pivot table is subject to have a limited number of rows of a spreadsheet data sheet. In another embodiment, the data table on which a pivot table is subject to can exceed the limit of the number of rows of a spreadsheet data sheet.

US Patent:

20130290150, Oct 31, 2013

Filed:

Apr 27, 2012

Appl. No.:

13/458151

Inventors:

Dilip Patel - Edison NJ, US

International Classification:

G06Q 10/08

US Classification:

705 28

Abstract:

Optimum Inventory Management is important in a variety of applications ranging from managing stocks of consumer perishables of a supermarket chain to managing number of magazines to be distributed to retail stores. Currently inventory decision making are done at certain segment or bucket level, thus making the implementation sub-optimal. In this invention, we develop a method and a system for performing analysis at much finer level of granularity. Moreover, widely used inventory models are not capable of handling the display effect and its interaction with price. Inventory decision making at customized scenarios is accomplished by leveraging business intelligence software that allow one to write scripts to perform real-time analysis under user specified input parameters. Inventory optimization at finer level of granularity is accomplished using a model that incorporates various drivers including the display and price effects, and latest statistical techniques to estimate the model with historical data.