Abstract: Techniques are described for receiving data generated by multiple platforms of different types, and managing the data in multiple stages of a data lifecycle associated with a super-platform. An end-user (e.g., data discloser) may interact with multiple individual (e.g., siloed) platforms of different types. The individual platforms may generate data describing, and/or resulting from, these interactions with end-user(s). The data from the various individual platforms may be received, ingested, stored, analyzed, aggregated, and/or otherwise processed by a super-platform during various stages of a data lifecycle. In some implementations, the end-user, the super-platform, and/or the individual platform(s) may provide one or more restrictions on how the data may be handled in each of the stages of the data lifecycle.

Abstract: Techniques are described for receiving data generated by multiple platforms of different types, and managing the data in multiple stages of a data lifecycle associated with a super-platform. An end-user (e.g., data discloser) may interact with multiple individual (e.g., siloed) platforms of different types. The individual platforms may generate data describing, and/or resulting from, these interactions with end-user(s). The data from the various individual platforms may be received, ingested, stored, analyzed, aggregated, and/or otherwise processed by a super-platform during various stages of a data lifecycle. In some implementations, the end-user, the super-platform, and/or the individual platform(s) may provide one or more restrictions on how the data may be handled in each of the stages of the data lifecycle.