Abstract: Dynamic determination of video correlation is disclosed, including: obtaining a plurality of recorded video interactions; obtaining a plurality of recorded non-video interactions; storing, at a database, event data determined based at least in part on the plurality of recorded video interactions and the plurality of recorded non-video interactions; and determining a subset of the event data that comprises correlations between a video and non-video interactions.

Abstract: Efficient uniques querying is disclosed, including: receiving a search query for a number of unique audience members across a plurality of groups of audience members; obtaining a plurality of sets of representations corresponding to respective ones of the plurality of groups of audience members; selecting at least a subset from each of the plurality of sets of representations; merging the selected at least subsets of the plurality of sets of representations into a merged set of representations; determining the number of unique audience members across the plurality of groups of audience members based at least in part on the merged set of representations; and outputting the number of unique audience members across the plurality of groups of audience members.

Abstract: Efficient aggregation of time series data is disclosed, including: obtaining a first entry value corresponding to an item, wherein the first entry value comprises a first recorded data point that is associated with a first time interval; generating a compressed block based at least in part on compressing the first entry value with at least a second entry value; storing the compressed block in a document corresponding to the item; determining that the item matches an aggregation search query; decompressing the compressed block from the document corresponding to the item to obtain the first entry value and the second entry value; and generating an aggregation result in response to the aggregation search query based on at least a portion of the first entry value and the second entry value.

Abstract: Efficient aggregation of time series data is disclosed, including: obtaining a first entry value corresponding to an item, wherein the first entry value comprises a first recorded data point that is associated with a first time interval; generating a compressed block based at least in part on compressing the first entry value with at least a second entry value; storing the compressed block in a document corresponding to the item; determining that the item matches an aggregation search query; decompressing the compressed block from the document corresponding to the item to obtain the first entry value and the second entry value; and generating an aggregation result in response to the aggregation search query based on at least a portion of the first entry value and the second entry value.

Abstract: Efficient uniques querying is disclosed, including: receiving a search query for a number of unique audience members across a plurality of groups of audience members; obtaining a plurality of sets of representations corresponding to respective ones of the plurality of groups of audience members; selecting at least a subset from each of the plurality of sets of representations; merging the selected at least subsets of the plurality of sets of representations into a merged set of representations; determining the number of unique audience members across the plurality of groups of audience members based at least in part on the merged set of representations; and outputting the number of unique audience members across the plurality of groups of audience members.

Abstract: Determining a video audience is disclosed, including: identifying a set of videos based at least in part on a received criterion; querying a video database to retrieve engagements associated with each of at least a subset of the set of videos; identifying a set of audience members associated with the engagements associated with each of the at least subset of the set of videos; and querying a user database to gather events associated with each of at least a subset of the set of audience members.

Abstract: Determining a video audience is disclosed, including: identifying a set of videos based at least in part on a received criterion; querying a video database to retrieve engagements associated with each of at least a subset of the set of videos; identifying a set of audience members associated with the engagements associated with each of the at least subset of the set of videos; and querying a user database to gather events associated with each of at least a subset of the set of audience members.