Abstract: In at least one embodiment, a trust rating system and method provide a precise and accurate, structured (yet adaptable and flexible), quantifying way of expressing historical trustworthiness so the user or decision maker can make more informed decisions on the data or information being evaluated.

Abstract: Analytical methods and systems applied to sequential event data are disclosed. An exemplary system and method analyzes datasets containing events in a plurality of journeys. The methods and systems described analyze and quantify the relative importance of events and sequences leading to outcomes where the data is complex and interconnected. In some embodiments, a graphical user interface illustrates the quantification of these datasets. In some embodiments, the graphical user interface maps the journey paths to show the relative importance of each journey path. In some embodiments, the maps of journey paths are interactive, allowing selection of paths of interest for detailed analysis. In some embodiments, the methods and systems calculate paths similar to a journey path of interest. An exemplary method and system also provides detailed recommendations for changing events within a sequence to either increase or decrease the likelihood of achieving a selected outcome.

Abstract: In an embodiment, the a method is provided. The method includes receiving forecast data in a database with an associated window value. The method also includes accessing data based on associated window values. The method further includes comparing the data accessed based on associated window values to other data.

Abstract: In an embodiment a method is provided. The method includes receiving forecast information in a computer from a first group of users. The method also includes integrating the forecast information into a database and corresponding OLAP cube accessible by the computer. The method further includes receiving comments on specific entries of the forecast information in the computer from a second group of users. The method also includes receiving changes of the forecast information in the computer from a second group of users The method further includes integrating comments and changes into the database and OLAP cube. Moreover, the method includes providing a display of the comments and the changes to the first group of users in an interface to the computer.

Abstract: The present invention relates to computerized (“smart”) mobile electronic devices and more particularly, to a system and methods of diagnosing and repairing malfunctions in smart mobile electronic devices, including a diagnostic process that utilizes decisions based on Big Data that holds information of multiple devices and offers a “disable components” (i.e., turn-off components) solution in order to overcome the problem without flashing a firmware or doing a factory-reset.

Abstract: In an embodiment a method is provided. The method includes receiving forecast information in a computer from a first group of users. The method also includes integrating the forecast information into a database and corresponding OLAP cube accessible by the computer. The method further includes receiving comments on specific entries of the forecast information in the computer from a second group of users. The method also includes receiving changes of the forecast information in the computer from a second group of users The method further includes integrating comments and changes into the database and OLAP cube. Moreover, the method includes providing a display of the comments and the changes to the first group of users in an interface to the computer.

Abstract: In an embodiment, the a method is provided. The method includes receiving forecast data in a database with an associated window value. The method also includes accessing data based on associated window values. The method further includes comparing the data accessed based on associated window values to other data.

Abstract: In one embodiment, a system is provided. The system includes a first client. The system also includes an analysis server coupled to the first client. The system further includes a first customer database of information coupled to the analysis server. The first customer database is to embody forecast data and to receive essentially real-time updates to the forecast data. The first customer database supports an OLAP cube associated with the analysis server.

Abstract: In an embodiment a method is provided. The method includes receiving forecast information in a computer from a first group of users. The method also includes integrating the forecast information into a database and corresponding OLAP cube accessible by the computer. The method further includes receiving comments on specific entries of the forecast information in the computer from a second group of users. The method also includes receiving changes of the forecast information in the computer from a second group of users The method further includes integrating comments and changes into the database and OLAP cube. Moreover, the method includes providing a display of the comments and the changes to the first group of users in an interface to the computer.

Abstract: In one embodiment, a method is provided. The method includes receiving forecast information from sales people in a computer. The method further includes receiving comments on specific entries of the forecast information from non-sales people in the computer. The method also includes receiving changes of the forecast information from the non-sales people in the computer. The method additionally includes providing a display of the comments and the changes to the sales people in an interface to the computer.

Abstract: In one embodiment, a system is provided. The system includes a first client. The system also includes an analysis server coupled to the first client. The system further includes a first customer database of information coupled to the analysis server. The first customer database is to embody forecast data and to receive essentially real-time updates to the forecast data. The first customer database supports an OLAP cube associated with the analysis server.

Abstract: The present invention relates to computerized (“smart”) mobile electronic devices and more particularly, to a system and methods of diagnosing and repairing malfunctions in smart mobile electronic devices, including a diagnostic process that utilizes decisions based on Big Data that holds information of multiple devices and offers a “disable components” (i.e., turn-off components) solution in order to overcome the problem without flashing a firmware or doing a factory-reset.

Abstract: The present invention relates to computerized (“smart”) mobile electronic devices and more particularly, to a system and methods of diagnosing and repairing malfunctions in smart mobile electronic devices, including a diagnostic process that utilizes decisions based on Big Data that holds information of multiple devices and offers a “disable components” (i.e., turn-off components) solution in order to overcome the problem without flashing a firmware or doing a factory-reset.

Abstract: In an embodiment a method is provided. The method includes receiving forecast information in a computer from a first group of users. The method also includes integrating the forecast information into a database and corresponding OLAP cube accessible by the computer. The method further includes receiving comments on specific entries of the forecast information in the computer from a second group of users. The method also includes receiving changes of the forecast information in the computer from a second group of users The method further includes integrating comments and changes into the database and OLAP cube. Moreover, the method includes providing a display of the comments and the changes to the first group of users in an interface to the computer.

Abstract: Analytical methods and systems applied to sequential event data are disclosed. An exemplary system and method analyzes datasets containing events in a plurality of journeys. The methods and systems described analyze and quantify the relative importance of events and sequences leading to outcomes where the data is complex and interconnected. In some embodiments, a graphical user interface illustrates the quantification of these datasets. In some embodiments, the graphical user interface maps the journey paths to show the relative importance of each journey path. In some embodiments, the maps of journey paths are interactive, allowing selection of paths of interest for detailed analysis. In some embodiments, the methods and systems calculate paths similar to a journey path of interest. An exemplary method and system also provides detailed recommendations for changing events within a sequence to either increase or decrease the likelihood of achieving a selected outcome.

Abstract: In an embodiment, the a method is provided. The method includes receiving forecast data in a database with an associated window value. The method also includes accessing data based on associated window values. The method further includes comparing the data accessed based on associated window values to other data.

Abstract: Analytical methods and systems applied to sequential event data are disclosed. An exemplary system and method analyzes datasets containing events in a plurality of journeys. The methods and systems described analyze and quantify the relative importance of events and sequences leading to outcomes where the data is complex and interconnected. In some embodiments, a graphical user interface illustrates the quantification of these datasets. In some embodiments, the graphical user interface maps the journey paths to show the relative importance of each journey path. In some embodiments, the maps of journey paths are interactive, allowing selection of paths of interest for detailed analysis. In some embodiments, the methods and systems calculate paths similar to a journey path of interest. An exemplary method and system also provides detailed recommendations for changing events within a sequence to either increase or decrease the likelihood of achieving a selected outcome.

Abstract: In one embodiment, a method is provided. The method includes receiving forecast information from sales people in a computer. The method further includes receiving comments on specific entries of the forecast information from non-sales people in the computer. The method also includes receiving changes of the forecast information from the non-sales people in the computer. The method additionally includes providing a display of the comments and the changes to the sales people in an interface to the computer.