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 1,500+ 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](/_next/image?url=%2Fdocs%2Fscreenshot%2F2023-11-13-data-inventory-datapoints.png&w=3840&q=75)