Abstract: A system and method for performing click stream analysis is described. In one implementation, a Web log is processed to reconstruct a visit made by a user to a Web site. The Web log contains records representing actions performed by the user during the visit including any actions that may be designated a commerce event. A sequential identification is assigned to each record and the sequential identification is stored with the associated record in a database. Any records representing actions performed by the user that are designated as a commerce event are identified. The database is queried for a certain quantity of records representing actions performed by the user prior to and/or subsequent to the commerce event, based on the sequential identification assigned to each record.

Abstract: Instance data is transmitted for Payload/Milestone events and for Enable-Continuation events. Payload/Milestone event data contains information describing an instance and/or providing a time of one or more portions of the processing of an instance. Included in the Enable-Continuation event data is an identifier associated with an instance by a first application and an identifier associated with the same instance by another application. The identifiers are placed in a continuation data table which is used to index the appropriate record of an instance data table. Out-of-order data for an instance is hidden from view until sequentially prior data for the instance is received.

Abstract: Multiple aggregation groups, which can be multiple partitions in an aggregated data table, are formed. Each group includes multiple aggregation records; each aggregation record includes an aggregation of values contained by a different subset of multiple database records. While an aggregation group is accessed by a single program thread during an aggregation group update transaction, no other threads are allowed to access that group. The aggregation groups are combined into a single table of aggregation records. Each of the multiple database records may correspond to an instance of an organizational activity and include a field having a value indicating the corresponding instance to be in one of several process states. Each aggregation group may further include time-sorted aggregation records, each time-sorted aggregation record containing an aggregation value for instances in one of the several process states during a time period associated with the time-sorted aggregation record.

Abstract: Challenges associated with maintaining information about multiple instances of an activity are addressed. Separate database tables are maintained for data corresponding to active instances of an organization's activities and for data corresponding to inactive instances of an organization's activities. Multiple database tables can be maintained for data corresponding to inactive instances of an activity. In another aspect, data from the active instances table and one or more inactive instances tables are processed to generate combined analysis data.

Abstract: A system and method for performing click stream analysis is described. In one implementation, a Web log is processed to reconstruct a visit made by a user to a Web site. The Web log contains records representing actions performed by the user during the visit including any actions that may be designated a commerce event. A sequential identification is assigned to each record and the sequential identification is stored with the associated record in a database. Any records representing actions performed by the user that are designated as a commerce event are identified. The database is queried for a certain quantity of records representing actions performed by the user prior to and/or subsequent to the commerce event, based on the sequential identification assigned to each record.