Transcend integrations are built to support all three product lines across the platform: Data Mapping, Privacy Requests, and Consent. Transcend has the largest ecosystem of , 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
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
phone number would each be considered the individual subdatapoints of the
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.
Transcend Data Mapping auto-generates a company's Data Inventory: a centralized, up-to-date catalog of your company's systems (represented as data silos) and personal data (represented as datapoints and subdatapoints).
A company's Data Inventory view starts with data silos, which can be included in a few ways:
1. Manually added: when a Transcend user adds a silo to a list. Once added, this is an unconnected integration.
3. Automatically discovered: Transcend Data Mapping automatically identifies and recommends silos that a company should add and then connect.
Transcend Data Mapping also provides discovery and classification functionality through plugins. There are two types of plugins that can be built into an integration:
1. Silo Discovery:
One of the biggest challenges in data visibility and maintaining a unified, up-to-date Data Inventory is identifying which data silos need to be included. This challenge grows exponentially harder as businesses grow—with new tools added, procurement spread across distributed teams, changing system owners, etc.
Silo Discovery enables companies to automatically uncover new data silos and identify which data silos should be added to their Data Inventory. Data Silo Discovery plugins search a connected integration to identify any additional platforms and systems that share information with the original connected silo. Transcend uses the plugin to find these systems and recommend them as data silos to the customer. The customer can then approve these auto-recommended silos and add them to their Data Inventory, configure them for Privacy Requests, etc.
For example, AWS may have datapoints or subdatapoints relevant to personal data rights. However, since AWS has sever services within it, it is a powerful Silo Discovery Plugin:
2. Datapoint Schema Discovery:
Transcend Data Mapping also offers datapoint schema discovery by scanning and classifying unstructured or customizable platforms (e.g., a database). From that scan, Transcend then identifies and suggests the datapoints and subdatapoints likely to hold personal information.
Many SaaS data systems have clearly defined their datapoints and subdatapoints in their API architecture. However, for data systems with customizable architectures or varied implementation (e.g., internal databases, or SaaS with customizable schema, like Salesforce), it is challenging to predefine datapoints and Datapoint Schema Discovery can be particularly valuable in these instances.
Read more about Transcend Data Mapping here:
Companies need to honor individual data rights to comply with regulations like . Individuals exercise this right by submitting a DSR (data subject request) or privacy request to a company. Companies then need to access, delete, modify, etc. personal data across all of their systems, including SaaS vendors, data warehouses, and internal databases.
Transcend Privacy Requests automatically process these privacy requests across all systems within a company's tech stack. Transcend integrates with , making it easy for companies to connect their systems and begin processing requests.
To accurately find or delete information on a data subject, Transcend first needs to know what personal data it is looking for within a given system, or in other words, the datapoints. Datapoints defined in an integration have associated actions, allowing the integration to programmatically fulfill different types of privacy requests (e.g., access, erasure, opt out, etc.). These actions are commonly API requests that correspond with a type of privacy request. However, non-API integrations are supported for databases and data warehouse platforms as well. The types of privacy request actions included for each datapoint are dependent on the integrated system itself.
For example, System A stores information about their users. This is available on their API endpoint
/users. Transcend’s integration with System A is built with a datapoint for a user. The
/users endpoint allows 'get' requests, but not 'delete' requests. The
users datapoint in the integration would therefore include an action for access privacy requests, but not erasure.
In this way, a Transcend customer could connect hundreds of integrations and Transcend would fulfill all of their privacy requests programmatically.
Read more about Transcend Privacy Requests here:
Transcend integrates with tech partners by building onto their API and defining the datapoints, subdatapoints and API endpoints that have personal data and are relevant for privacy rights.
Transcend may use this integration to:
- programmatically process a company's privacy requests
- discover a company's data silos
- discover a company's datapoints or schema