Abstract: A novel approach to facilitating access to valuable actionable content from a multi-tenant database involves system generated ranking of connection content with associated data retrieval methods and systems, utilizing “connector” scores to rank responsive content. The system “learns” how to optimize retrieving and ranking high value actionable content with experience; and applies optimized scoring parameters to enhance future operations. The computer platform is greatly improved by delivering actionable content that is immediately translated into critical operations and tasks recommended by the system to support transactions for the User.

Abstract: A novel approach to facilitating access to valuable actionable content from a multi-tenant database involves system generated ranking of connection content with associated data retrieval methods and systems, utilizing “connector” scores to rank responsive content. The system “learns” how to optimize retrieving and ranking high value actionable content with experience; and applies optimized scoring parameters to enhance future operations. The computer platform is greatly improved by delivering actionable content that is immediately translated into critical operations and tasks recommended by the system to support transactions for the User.

Abstract: A novel approach to facilitating access to valuable actionable content from a multi-tenant database involves system generated ranking of connection content with associated data retrieval methods and systems, utilizing “connector” scores to rank responsive content. The system “learns” how to optimize retrieving and ranking high value actionable content with experience; and applies optimized scoring parameters to enhance future operations. The computer platform is greatly improved by delivering actionable content that is immediately translated into critical operations and tasks recommended by the system to support transactions for the User.

Abstract: Write back to customer relationship management systems is provided. Data logging of activities can be performed for sales professionals that use other third-party software solutions during their selling process. The logged data can be written back to the CRM system instead of needing input by the sales professionals. Certain data and generated insights can be written back to further enhance the data available to clients' sales organizations. Capability of writing back to target CRM systems can leverage existing APIs. Identification of data to be written back to the CRM systems is performed by an intelligent write back (IWB) system. The IWB system will write back to the standard objects in tenant CRMs. The IWB system can create custom fields within those objects for write back data.

Abstract: Large-scale advanced database models, systems, and methods provide a responsive, scalable data storage solution which is ripe for use in data warehousing and analytics environments. These advanced database models, systems, and methods provide for dramatically increased performance in accessing data as well as increased storage capabilities in the data set.

Abstract: Disclosed embodiments include methods and systems for utilizing a structured projection pattern to perform depth detection. In some instances, the structured projection pattern forms a dot pattern, which is projected by a projector, wherein the projector includes one or more infrared (IR) light dot pattern illuminators for projecting an IR light dot pattern to a surrounding environment. The IR dot pattern light that is at least partially reflected off one or more objects in the surrounding environment is detected by one or more cameras attached to a head-mounted display (HMD). The HMD, which is physically untethered from the projector, utilizes the captured IR dot pattern light reflections to track movement of the HMD and/or perform depth detection of one or more objects in the environment surrounding the HMD.

Abstract: A first image and a second image of a scene are obtained for use in detecting the location of the floor in the scene. A first of the images is mapped onto a candidate plane that is perpendicular to a gravity vector, thereby creating a texture-mapped plane. The texture-mapped plane is projected into the geometry of the camera utilized to take the second image to create an artificial first image. A comparison is then performed between the first image and the artificial first image to generate a similarity score. Multiple candidate planes are processed in this manner for the first and second images, and the candidate plane generating the highest associated similarity score is chosen as the floor. This process can be repeated for multiple sets of stereo images.

Abstract: Disclosed embodiments include methods and systems for utilizing a structured projection pattern to perform depth detection. In some instances, the structured projection pattern forms a dot pattern, which is projected by a projector, wherein the projector includes one or more infrared (IR) light dot pattern illuminators for projecting an IR light dot pattern to a surrounding environment. The IR dot pattern light that is at least partially reflected off one or more objects in the surrounding environment is detected by one or more cameras attached to a head-mounted display (HMD). The HMD, which is physically untethered from the projector, utilizes the captured IR dot pattern light reflections to track movement of the HMD and/or perform depth detection of one or more objects in the environment surrounding the HMD.

Abstract: A first image and a second image of a scene are obtained for use in detecting the location of the floor in the scene. A first of the images is mapped onto a candidate plane that is perpendicular to a gravity vector, thereby creating a texture-mapped plane. The texture-mapped plane is projected into the geometry of the camera utilized to take the second image to create an artificial first image. A comparison is then performed between the first image and the artificial first image to generate a similarity score. Multiple candidate planes are processed in this manner for the first and second images, and the candidate plane generating the highest associated similarity score is chosen as the floor. This process can be repeated for multiple sets of stereo images.

Abstract: A system for determining distances to features in a scene is disclosed. The system includes, among other features, a target portion identifier module, a target surface generator, a reflector selection module, a light transport simulation module, a depth measurement correction generation module, and a distance calculation module. The target portion identifier module is configured to identify a plurality of target portions of the scene. The target surface generator is configured to simulate a plurality of target surfaces. The reflector selection module is configured to select a first plurality of reflector surfaces from the plurality of target surfaces and a second plurality of reflector surfaces from the first plurality of reflector surfaces.

Abstract: Large-scale advanced database models, systems, and methods provide a responsive, scalable data storage solution which is ripe for use in data warehousing and analytics environments. These advanced database models, systems, and methods provide for dramatically increased performance in accessing data as well as increased storage capabilities in the data set.

Abstract: Large-scale advanced database models, systems, and methods provide a responsive, scalable data storage solution which is ripe for use in data warehousing and analytics environments. These advanced database models, systems, and methods provide for dramatically increased performance in accessing data as well as increased storage capabilities in the data set.

Abstract: A computing system includes memory storing executable instructions and one or more processors operatively connected to the memory. The one or more processors execute the executable instructions to effectuate a method. The method may include (i) analyzing raw data obtained from a plurality of different data sources in order to identify one or more data structures of the raw data and to tag data identifying at least one of the plurality of different data sources; and (ii) generating a plurality of Universal Data Model (UDM) constructs. Each UDM construct may be based at least in part on the identified data structure(s) of the raw data. Each UDM construct may exclude the tagged data identifying at least one of the plurality of different data sources. Each UDM construct may organize the raw data into a particular arrangement of rows and columns.

Abstract: Large-scale advanced database models, systems, and methods provide a responsive, scalable data storage solution which is ripe for use in data warehousing and analytics environments. These advanced database models, systems, and methods provide for dramatically increased performance in accessing data as well as increased storage capabilities in the data set.

Abstract: Among other things, one or more techniques and/or systems are provided for defining transition zones for navigating a visualization. The visualization may be constructed from geometry of a scene and one or more texture images depicted the scene from various viewpoints. A transition zone may correspond to portions of the visualization that do not have a one-to-one correspondence with a single texture image, but are generated from textured geometry (e.g., a projection of texture imagery onto the geometry). Because a translated view may have visual error (e.g., a portion of the translated view is not correctly represented by the textured geometry), one or more transition zones, specifying translated view experiences (e.g., unrestricted view navigation, restricted view navigation, etc.), may be defined. For example, a snapback force may be applied when a current view corresponds to a transition zone having a relatively higher error.

Abstract: A computing system includes memory comprising executable instructions and one or more processors operatively connected to the memory and configured to execute the executable instructions in order to effectuate a method. The method may include (i) analyzing raw data obtained from a plurality of different data sources in order to identify one or more data structures of the raw data and to tag data identifying at least one of the plurality of different data sources; and (ii) generating a plurality of Universal Data Model (UDM) constructs. Each UDM construct may be based at least in part on the identified one or more data structures of the raw data and each UDM construct may exclude the tagged data identifying at least one of the plurality of different data sources. Each UDM construct may organize the raw data into a particular arrangement of at least one row and at least one column.

Abstract: Large-scale advanced database models, systems, and methods provide a responsive, scalable data storage solution which is ripe for use in data warehousing and analytics environments. These advanced database models, systems, and methods provide for dramatically increased performance in accessing data as well as increased storage capabilities in the data set.

Abstract: A non-transitory computer-readable medium includes executable instructions that when executed by a processor cause the processor to effectuate a method. The method may include obtaining raw data from a plurality of different data sources; analyzing the raw data to identify one or more data structures of the raw data and to tag data identifying at least one of the plurality of different data sources; generating a plurality of Universal Data Model (UDM) constructs, each UDM construct being based at least in part on the one or more data structures of the raw data and each UDM construct excluding the source-identifying data.

Abstract: A non-transitory computer-readable medium is disclosed comprising executable instructions that when executed by a processor cause the processor to effectuate a method comprising the steps of: obtaining raw data from a plurality of different data sources; analyzing the raw data to identify one or more data structures of the raw data and to tag data identifying at least one of the plurality of different data sources; generating a plurality of Universal Data Model (UDM) constructs, each UDM being based at least in part on the one or more data structures of the raw data and each UDM excluding the source-identifying data; redacting the source-identifying data from the raw data to generate anonymous raw data; and generating anonymous UDM transformed data by integrating the anonymous raw data by extracting, transforming, and loading the anonymous raw data such that the anonymous raw data conforms to the UDM construct.

Abstract: Among other things, one or more techniques and/or systems are provided for defining transition zones for navigating a visualization. The visualization may be constructed from geometry of a scene and one or more texture images depicted the scene from various viewpoints. A transition zone may correspond to portions of the visualization that do not have a one-to-one correspondence with a single texture image, but are generated from textured geometry (e.g., a projection of texture imagery onto the geometry). Because a translated view may have visual error (e.g., a portion of the translated view is not correctly represented by the textured geometry), one or more transition zones, specifying translated view experiences (e.g., unrestricted view navigation, restricted view navigation, etc.), may be defined. For example, a snapback force may be applied when a current view corresponds to a transition zone having a relatively higher error.