# Understanding Integrations: Datapoints (/docs/overview/understanding-integrations/understanding-integrations-datapoints)

Transcend integrations are built to support product lines across the platform: System Discovery, Structured Discovery, Unstructured Discovery, DSR Automation, and Consent Management. Transcend has the largest ecosystem of [1,500+ integrations](https://transcend.io/integrations), with all integration code built and managed in-house.

## Datapoints and subdatapoints [#datapoints-and-subdatapoints]

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 systems 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 systems, datapoints, and subdatapoints](/images/screenshot/2023-11-13-data-inventory-datapoints.png)