Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating derived dimensions within ingested data collections. In particular, in one or more embodiments, the disclosed systems generate derived dimensions that modify or correct one or more organizational schemas of an ingested data collection when querying the ingested data collection. For example, the disclosed systems receive a user-defined definition, and generates a fallback expression based on the user-defined definition and aligned to the schema of a particular ingested data collection. In at least one embodiment, the disclosed systems generate the derived dimension by identifying and modifying one or more existing dimensions in the schema based on the fallback expression when reading data from the ingested data collection.

Abstract: This disclosure generally covers systems and methods that create sequential segments from analytics data to enable investigation of events that occurred before or after a certain sequence of events—that is, pre-sequence or post-sequence events. In particular, certain embodiments of the disclosed systems and methods receive a segment query of certain analytics data to identify events that occurred before or after a defined sequence of events within a network and—in response to the segment query—provide a query result that identifies pre-sequence events or post-sequence events. By providing such query results, the disclosed systems and methods enable users to examine correlations between a sequence of events and any pre-sequence or post-sequence events, including any data associated with those events at a granular level.

Abstract: The present disclosure is directed toward systems and methods that allow users to efficiently and effectively create and identify segments of usage patterns. For example, systems and methods described herein allow marketers to query and return sequential segments including sequence conditions based on user-defined dimension item values. Furthermore, systems and methods described allow marketers to query and return sequential segments including sequential events based on user-defined dimension variables. In addition to the foregoing, systems and methods described herein allow marketers to query and return sequential segments defined by repeated events performed at given regularity or frequency.

Abstract: This disclosure generally covers systems and methods that create sequential segments from analytics data to enable investigation of events that occurred before or after a certain sequence of events—that is, pre-sequence or post-sequence events. In particular, certain embodiments of the disclosed systems and methods receive a segment query of certain analytics data to identify events that occurred before or after a defined sequence of events within a network and—in response to the segment query—provide a query result that identifies pre-sequence events or post-sequence events. By providing such query results, the disclosed systems and methods enable users to examine correlations between a sequence of events and any pre-sequence or post-sequence events, including any data associated with those events at a granular level.

Abstract: Methods and apparatus are presented for flexibly building a dynamic report using a heterogeneous mix of dimensions, segments, and metrics. Within a report building tool a user may introduce any number of dimensions and segments at any point within a generated report. Further within the report building tool, a user may break down existing dimensions and segments within a report with nested dimensions and segments, which may be added without limits on a nesting level. Given a generated report, a user may pivot the generated report, where the pivot includes pivoting any heterogeneous combination of dimensions, segments, and metrics within the generated report defined along each axis. Further, the pivot operation maintains the relative groupings and nestings of dimensions, dimension items, segments, and metrics in going from a column to a row or from a row to a column.

Abstract: This disclosure generally covers systems and methods that create sequential segments from analytics data to enable investigation of events that occurred before or after a certain sequence of events—that is, pre-sequence or post-sequence events. In particular, certain embodiments of the disclosed systems and methods receive a segment query of certain analytics data to identify events that occurred before or after a defined sequence of events within a network and—in response to the segment query—provide a query result that identifies pre-sequence events or post-sequence events. By providing such query results, the disclosed systems and methods enable users to examine correlations between a sequence of events and any pre-sequence or post-sequence events, including any data associated with those events at a granular level.

Abstract: Methods and apparatus are presented for flexibly building a dynamic report using a heterogeneous mix of dimensions, segments, and metrics. Within a report building tool a user may introduce any number of dimensions and segments at any point within a generated report. Further within the report building tool, a user may break down existing dimensions and segments within a report with nested dimensions and segments, which may be added without limits on a nesting level. Given a generated report, a user may pivot the generated report, where the pivot includes pivoting any heterogeneous combination of dimensions, segments, and metrics within the generated report defined along each axis. Further, the pivot operation maintains the relative groupings and nestings of dimensions, dimension items, segments, and metrics in going from a column to a row or from a row to a column.

Abstract: Methods and apparatus are presented for flexibly building a dynamic report using a heterogeneous mix of dimensions, segments, and metrics. Within a report building tool a user may introduce any number of dimensions and segments at any point within a generated report. Further within the report building tool, a user may break down existing dimensions and segments within a report with nested dimensions and segments, which may be added without limits on a nesting level. Given a generated report, a user may pivot the generated report, where the pivot includes pivoting any heterogeneous combination of dimensions, segments, and metrics within the generated report defined along each axis. Further, the pivot operation maintains the relative groupings and nestings of dimensions, dimension items, segments, and metrics in going from a column to a row or from a row to a column.

Abstract: The present disclosure is directed toward systems and methods that allow users to efficiently and effectively create and identify segments of usage patterns. For example, systems and methods described herein allow marketers to query and return sequential segments including sequence conditions based on user-defined dimension item values. Furthermore, systems and methods described allow marketers to query and return sequential segments including sequential events based on user-defined dimension variables. In addition to the foregoing, systems and methods described herein allow marketers to query and return sequential segments defined by repeated events performed at given regularity or frequency.

Abstract: Methods and apparatus are presented for flexibly building a dynamic report using a heterogeneous mix of dimensions, segments, and metrics. Within a report building tool a user may introduce any number of dimensions and segments at any point within a generated report. Further within the report building tool, a user may break down existing dimensions and segments within a report with nested dimensions and segments, which may be added without limits on a nesting level. Given a generated report, a user may pivot the generated report, where the pivot includes pivoting any heterogeneous combination of dimensions, segments, and metrics within the generated report defined along each axis. Further, the pivot operation maintains the relative groupings and nestings of dimensions, dimension items, segments, and metrics in going from a column to a row or from a row to a column.