Understanding Integrations: Datapoints

Transcend integrations are built to support product lines across the platform: Silo Discovery, Structured Discovery, Unstructured Discovery, DSR Automation, and Consent Management. Transcend has the largest ecosystem of 1,300+ integrations, with all integration code built and managed in-house.

Each integration is built with a defined set of datapoints that represent information stored in another system that contains personal information and subject to privacy laws.

Datapoints represent an object containing a person's data. For example, a user or customer could be a datapoint representing a person, where a activity log or email history could be datapoints that represent an object containing a person's data.

Within each integration, Transcend identifies and incorporates the datapoints relevant to data rights and privacy requirements.

Datapoints often contain additional relevant information as properties of a datapoint or subdatapoints. For example, a name, email and phone number would each be considered the individual subdatapoints of the user datapoint.

While data silos represent the high level view of the technologies used by a company, the datapoints and subdatapoints for each integration provide a detailed breakdown of all personal information kept in all systems used.

Diagram showing relationships between data silos, datapoints, and subdatapoints