Whether your device graph methodology is Deterministic or Probablistic Device Graphs rely on matching key identifiers within detailed log level data and associating them with identities. Whenever these key identifiers appear in your device graph data set, your device Graph recognizes them as tied to a particular identity.
aGraph recognizes sets of identifiers in both inbound, and onboarded data sets and then applies the identity associated with them to records where they are present.
The process can also work to extend the reach of User identities established by your own business analysis. Proliferate your own Identifiers within 3rd party device Graphs and data sets to increase the value of your privately maintained 1st party data insights.
aqfer Graph realizes Integration of deterministic evidence and 3rd party device graphs
ID sync and onboarding events generate deterministic edges
aqfer Graph generates probabilistic edges and inferred entities to connect with deterministic data in the data lake
Protocols: API protocols are part of aqfer.IO graph API for discrete graph access. For bulk graph access our clients typically use SPARK graph frames
Data Models: Starting point schema provided can be customized to your needs.
aqfer Tag Manager aqfer Data Lake aqfer IO