Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: Methods and apparatuses for organizations to monitor, analyze and respond to unstructured and structured data that is related to their Governance, Risk, and Compliance (GRC) programs. Embodiments of the invention generated mapped Risk Control Matrices (RCMs) and/or insights for improving the GRC process from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create attributes and contributors. The attributes and weighted contributors are processed to form mapped RCMs and/or GRC-related insights.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: Methods and apparatus for modeling, using a data science approach, the propensity of employee turn-over and the level of engagement of employees. Both unstructured and structured data from internal and external sources are included in the analysis to determine the level of satisfaction and contribution by employees. What-if analysis permits assessment of the impact on satisfaction, contribution and/or budget for various what-if scenarios, permitting management to take the most effective action to drive retention and/or employee contribution goals.

Abstract: Methods and apparatuses for organizations to monitor, analyze and respond to unstructured and structured data that is related to their Governance, Risk, and Compliance (GRC) programs. Embodiments of the invention generated mapped Risk Control Matrices (RCMs) and/or insights for improving the GRC process from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create attributes and contributors. The attributes and weighted contributors are processed to form mapped RCMs and/or GRC-related insights.

Abstract: Techniques for providing information describing how users are funneling through various products and features of a website are described. According to various embodiments, a user specification of a first set of one or more entities is received. A user interface element is then displayed, the user interface element indicating an amount of total online user sessions that include user interactions with at least one of the entities in the first set during a specific time interval. Thereafter, a user specification of a second set of one or more entities is received. A second user interface element is then displayed, the second user interface element indicating a subset of the total online user sessions that include user interactions with at least one of the entities in the second set subsequent to the user interactions with at least one of the entities in the first set.

Abstract: Techniques for providing information describing how users are funneling through various products and features of a website are described. According to various embodiments, a user specification of a first set of one or more entities is received. A data structure storing a plurality of data structure entities is then accessed, each of the data structure entities corresponding to an online user session and describing one or more user interaction events included in the corresponding online user session. A set of the plurality of data structure entities are then retrieved from the data structure, the set of the plurality of data structure entities corresponding to online user sessions that include a user interaction event with at least one of the entities in the first set. Information regarding the retrieved set of the plurality of data structure entities is then provided to a user, via a user interface.

Abstract: A method and system for displaying predictions on a spatial map includes using a data analyzer for analyzing heterogeneous data having a spatial component to find utilizable data and using machine learning to automatically extract relationships from the utilizable data. The extracted relationships are used to make a prediction about at least one location on the spatial map and present that prediction in an oblique or perspective view. An interface presents the prediction on the spatial map in the form of a heat map overlying a 3-D topographical map. Although the 3-D map can be shown as any form of graphical projection including an oblique projection or orthographic projection, preferably a perspective view is used. It is also preferred that the graphical projection be interactive. The heat map may be 2-D or 3-D and be selectively displayed depending on the preference of a user.

Abstract: A method and system for displaying predictions on a spatial map includes using a data analyzer for analyzing heterogeneous data having a spatial component to find utilizable data and using machine learning to automatically extract relationships from the utilizable data. The extracted relationships are used to make a prediction about at least one location on the spatial map and present that prediction in an oblique or perspective view. An interface presents the prediction on the spatial map in the form of a heat map overlying a 3-D topographical map. Although the 3-D map can be shown as any form of graphical projection including an oblique projection or orthographic projection, preferably a perspective view is used. It is also preferred that the graphical projection be interactive. The heat map may be 2-D or 3-D and be selectively displayed depending on the preference of a user.