Abstract: This disclosure involves using data science notebooks to customize and apply a visitor stitching framework. An event management system provides an initial visitor stitching framework via a data science notebook, wherein the data science notebook is an interactive environment for managing algorithms and data. The event management system receives, from a resource provider system via the data science notebook, a modification to the initial visitor stitching framework. The event management system applies the modification to the initial visitor stitching framework to generate a custom visitor stitching framework. The event management system processes a dataset associated with the resource provider system and a user using the custom visitor stitching framework to generate a stitched dataset associated with the user.

Abstract: This disclosure involves stitching event data using identity mappings. An event analytics system generates and stores an event dataset including first event data for a first set of events associated with a user. The first event data includes timestamps and a device identifier. The system identifies second event data for a second event associated with the user. The second event data includes a timestamp, the device identifier, and a user identifier. The system appends the second event data to the event dataset. Based on the second event data, the system generates and stores an identity mapping that maps the device identifier to the user identifier. Based on the identity mapping and a predetermined look-back window, the system updates the first event data to include the user identifier.

Abstract: This disclosure involves using data science notebooks to customize and apply a visitor stitching framework. An event management system provides an initial visitor stitching framework via a data science notebook, wherein the data science notebook is an interactive environment for managing algorithms and data. The event management system receives, from a resource provider system via the data science notebook, a modification to the initial visitor stitching framework. The event management system applies the modification to the initial visitor stitching framework to generate a custom visitor stitching framework. The event management system processes a dataset associated with the resource provider system and a user using the custom visitor stitching framework to generate a stitched dataset associated with the user.

Abstract: This disclosure involves stitching event data using identity mappings. An event analytics system generates and stores an event dataset including first event data for a first set of events associated with a user. The first event data includes timestamps and a device identifier. The system identifies second event data for a second event associated with the user. The second event data includes a timestamp, the device identifier, and a user identifier. The system appends the second event data to the event dataset. Based on the second event data, the system generates and stores an identity mapping that maps the device identifier to the user identifier. Asynchronously to generating and storing the event dataset, based on the identity mapping and a predetermined look-back window, the system updates the first event data to include the user identifier.

Abstract: This disclosure involves performing event analytics on-the-fly based on user input to an analysis interface. An event analytics system correlates a plurality of event datasets to include a common visitor identifier. The system causes display, via the analysis interface, of information about the plurality of event datasets. The system receives, via the analysis interface, user selection of one or more event datasets, of the plurality of event datasets. Based on the selected one or more event datasets, the system generates a combined event dataset. The event analytics system receives, via the analysis interface, user input specifying information requested about the combined event dataset. The system obtains the requested information about the combined event dataset. The system causes display, via the analysis interface, of a visualization of the obtained information, wherein the visualization is based on event data from the combined event dataset in chronological order.

Abstract: This disclosure involves performing event analytics on-the-fly based on user input to an analysis interface. An event analytics system correlates a plurality of event datasets to include a common visitor identifier. The system causes display, via the analysis interface, of information about the plurality of event datasets. The system receives, via the analysis interface, user selection of one or more event datasets, of the plurality of event datasets. Based on the selected one or more event datasets, the system generates a combined event dataset. The event analytics system receives, via the analysis interface, user input specifying information requested about the combined event dataset. The system obtains the requested information about the combined event dataset. The system causes display, via the analysis interface, of a visualization of the obtained information, wherein the visualization is based on event data from the combined event dataset in chronological order.

Abstract: This disclosure involves using data science notebooks to customize and apply a visitor stitching framework. An event management system provides an initial visitor stitching framework via a data science notebook, wherein the data science notebook is an interactive environment for managing algorithms and data. The event management system receives, from a resource provider system via the data science notebook, a modification to the initial visitor stitching framework. The event management system applies the modification to the initial visitor stitching framework to generate a custom visitor stitching framework. The event management system processes a dataset associated with the resource provider system and a user using the custom visitor stitching framework to generate a stitched dataset associated with the user.

Abstract: This disclosure involves stitching event data using identity mappings. An event analytics system generates and stores an event dataset including first event data for a first set of events associated with a user. The first event data includes timestamps and a device identifier. The system identifies second event data for a second event associated with the user. The second event data includes a timestamp, the device identifier, and a user identifier. The system appends the second event data to the event dataset. Based on the second event data, the system generates and stores an identity mapping that maps the device identifier to the user identifier. Asynchronously to generating and storing the event dataset, based on the identity mapping and a predetermined look-back window, the system updates the first event data to include the user identifier.