Abstract: Techniques and systems are described for analytics system entity resolution. Typed higher-order node combinations are determined within a dataset, and an amount of similarity between two arbitrary nodes within the dataset is determined based on the typed higher-order node combinations. The amount of similarity enables the digital analytics to accurately perform source resolution of portions of the dataset to a respective source, and may be utilized to control output of digital content to a client device.

Abstract: Offline consumer behavior and interactions are observed using beacons positioned at venues where consumers spend time and interact with each other. The beacons communicate with mobile computing devices that are carried by the observed consumers. The observed consumer behavior provides actionable insights into how consumers influence each other. For example, the people that a particular consumer spends time with form a “circle of influence” associated with that consumer. If the consumer makes a purchase, members of the circle of influence are observed to understand the degree to which they were influenced by the purchase, if at all. Metrics that quantify a consumer's influence over other consumers allow marketers to more effectively target both the influencing and influenced consumers. Also, if relatively little information is known about a particular consumer, that consumer's digital marketing profile can be supplemented using information known about the consumers with whom he/she often spends time.

Abstract: Techniques and systems are described for analytics system entity resolution. Typed higher-order node combinations are determined within a dataset, and an amount of similarity between two arbitrary nodes within the dataset is determined based on the typed higher-order node combinations. The amount of similarity enables the digital analytics to accurately perform source resolution of portions of the dataset to a respective source, and may be utilized to control output of digital content to a client device.

Abstract: Gauging consumer interest of in-person visitors is described. In one or more embodiments, a promotional apparatus having a display screen and a wireless beacon is deployed at a venue. The promotional apparatus presents a video having multiple video segments. During the presentation, the beacon and a mobile device of a venue visitor communicate wirelessly to determine a proximity of the visitor to the display screen. Multiple distances are determined at multiple times. A path of movement can be determined from the distances over time. If the visitor alters a direction of travel to veer toward the screen or stops walking close to the screen, a system infers that the video has engaged the visitor's attention. By linking particular video segments to times at which the mobile device is proximate to the display screen, the system can further infer consumer interest in specific product features being shown at those times.

Abstract: Offline consumer behavior and interactions are observed using beacons positioned at venues where consumers spend time and interact with each other. The beacons communicate with mobile computing devices that are carried by the observed consumers. The observed consumer behavior provides actionable insights into how consumers influence each other. For example, the people that a particular consumer spends time with form a “circle of influence” associated with that consumer. If the consumer makes a purchase, members of the circle of influence are observed to understand the degree to which they were influenced by the purchase, if at all. Metrics that quantify a consumer's influence over other consumers allow marketers to more effectively target both the influencing and influenced consumers. Also, if relatively little information is known about a particular consumer, that consumer's digital marketing profile can be supplemented using information known about the consumers with whom he/she often spends time.

Abstract: Offline consumer behavior and interactions are observed using beacons positioned at venues where consumers spend time and interact with each other. The beacons communicate with mobile computing devices that are carried by the observed consumers. The observed consumer behavior provides actionable insights into how consumers influence each other. For example, the people that a particular consumer spends time with form a “circle of influence” associated with that consumer. If the consumer makes a purchase, members of the circle of influence are observed to understand the degree to which they were influenced by the purchase, if at all. Metrics that quantify a consumer's influence over other consumers allow marketers to more effectively target both the influencing and influenced consumers. Also, if relatively little information is known about a particular consumer, that consumer's digital marketing profile can be supplemented using information known about the consumers with whom he/she often spends time.

Abstract: A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.

Abstract: A digital medium environment is described to determine textual content that is responsible for causing a viewing spike within a video. Video analytics data associated with a video is queried. The video analytics data identifies a number of previous user viewing s at various locations within the video. A viewing spike within the video is detected using the video analytics data. The viewing spike corresponds to an increase in the number of previous user viewings of the video that begins at a particular location within the video. Then, text of one or more video sources or video referral sources read by users prior to viewing the video from the particular location within the video is analyzed to identify textual content that is at least partially responsible for causing the viewing spike.

Abstract: Gauging consumer interest of in-person visitors is described. In one or more embodiments, a promotional apparatus having a display screen and a wireless beacon is deployed at a venue. The promotional apparatus presents a video having multiple video segments. During the presentation, the beacon and a mobile device of a venue visitor communicate wirelessly to determine a proximity of the visitor to the display screen. Multiple distances are determined at multiple times. A path of movement can be determined from the distances over time. If the visitor alters a direction of travel to veer toward the screen or stops walking close to the screen, a system infers that the video has engaged the visitor's attention. By linking particular video segments to times at which the mobile device is proximate to the display screen, the system can further infer consumer interest in specific product features being shown at those times.

Abstract: A digital medium environment is described to determine textual content that is responsible for causing a viewing spike within a video. Video analytics data associated with a video is queried. The video analytics data identifies a number of previous user viewing s at various locations within the video. A viewing spike within the video is detected using the video analytics data. The viewing spike corresponds to an increase in the number of previous user viewings of the video that begins at a particular location within the video. Then, text of one or more video sources or video referral sources read by users prior to viewing the video from the particular location within the video is analyzed to identify textual content that is at least partially responsible for causing the viewing spike.

Abstract: Offline consumer behavior and interactions are observed using beacons positioned at venues where consumers spend time and interact with each other. The beacons communicate with mobile computing devices that are carried by the observed consumers. The observed consumer behavior provides actionable insights into how consumers influence each other. For example, the people that a particular consumer spends time with form a “circle of influence” associated with that consumer. If the consumer makes a purchase, members of the circle of influence are observed to understand the degree to which they were influenced by the purchase, if at all. Metrics that quantify a consumer's influence over other consumers allow marketers to more effectively target both the influencing and influenced consumers. Also, if relatively little information is known about a particular consumer, that consumer's digital marketing profile can be supplemented using information known about the consumers with whom he/she often spends time.

Abstract: A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.

Abstract: Techniques are provided for transforming information about unique visits to a website or interactions with a mobile application by a single individual on different devices into unified analytical data representing these visits. One or more visitor stitching models can be used to quantify unique visits as belonging to the same person with a certain level of confidence. In addition to maintaining separate records for each unique visit, a unified record is generated, which represents a combination of the unique visits by the same person. Various analytics can then be performed on the unique and unified records. The unified records are favored over the separate data records wherever the stitching model corresponding to the unified record provides a certainty that meets or exceeds a user-specified confidence level. The visitor stitching model used for the analytics is considered non-committal because different models can be employed or none at all, depending on user preferences.

Abstract: A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.

Abstract: A method and apparatus for optimizing a backup chain using synthetic backups is described. In one embodiment, a method for creating synthetic incremental backups to optimize a backup chain comprises accessing a backup chain, which further comprises a plurality of incremental backups and determining schedule information defining a number of incremental backups to use to create one or more synthetic incremental backups representing the plurality of incremental backups from the backup chain, wherein the number of backups is defined by a numerical progression.

Abstract: A method, system, and computer-readable storage medium for managing backup operations of virtual machines are provided. According to one embodiment, a backup application initiates a snapshot of a storage volume, which stores a collection of virtual hard disk drives. A collection of virtual machines access the collection of virtual hard disk drives. The backup application accesses a collection of lists of changes to data. The collection of lists and the data are stored in the collection of virtual hard disk drives. A first list among the collection of lists is generated by a first virtual machine. The changes to data are made by the collection of virtual machines. The backup application generates an incremental backup of the first virtual hard disk drive by copying data from the snapshot in response to the first list identifying that the data changed subsequent to the generation of the prior backup.

Abstract: Techniques are provided for transforming information about unique visits to a website or interactions with a mobile application by a single individual on different devices into unified analytical data representing these visits. One or more visitor stitching models can be used to quantify unique visits as belonging to the same person with a certain level of confidence. In addition to maintaining separate records for each unique visit, a unified record is generated, which represents a combination of the unique visits by the same person. Various analytics can then be performed on the unique and unified records. The unified records are favored over the separate data records wherever the stitching model corresponding to the unified record provides a certainty that meets or exceeds a user-specified confidence level. The visitor stitching model used for the analytics is considered non-committal because different models can be employed or none at all, depending on user preferences.

Abstract: A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.

Abstract: A method and apparatus for optimizing a backup chain using synthetic backups is described. In one embodiment, a method for creating synthetic incremental backups to optimize a backup chain comprises accessing a backup chain, which further comprises a plurality of incremental backups and determining schedule information defining a number of incremental backups to use to create one or more synthetic incremental backups representing the plurality of incremental backups from the backup chain, wherein the number of backups is defined by a numerical progression.

Abstract: A first write operation is intercepted. The first write operation is a write from a virtual machine to a virtual disk. The first write operation is a change to a first data location. The change to the first data location is recorded. The recording creates a first change record. The first change record is stored separately from the first data location. A first backup operation is performed. The first backup operation, the intercepting, and the recording are performed by an application executing on a host of the virtual machine. The first backup operation includes a read request for the first data location. The read request for the first data location is fulfilled based on the first change record.