Data Inventory

Your Data Inventory is the base truth of all data in your company: data silos, the datapoints inside them, and metadata about what each datapoint represents. This is the system-level reality, and it powers other features across the Transcend platform, from keeping your ROPA live-updated to generating Consent rules for that newly-added advertising platform to encoding erasure logic in your data warehouse.

If you haven't gone through the Data Mapping Quickstart Guide, we recommend starting there for an overview.

With so many systems, it can be hard to track down exactly how each one is used. It's easier if you know who's responsible for that system. In Transcend, assign data silos to individuals within your organization. All you need to do is hover over the data silo row in Data Inventory and either enter the owner's name for existing Transcend users or enter the email of users who do not yet have a Transcend account—they'll receive an invitation with instructions.

A list of detected data silos with an owner field

The data silos within the in the Data Inventory, showing detected data silos.

Each data silo listed in Data Inventory has fields that help you understand your complete privacy footprint. We'll go through each to help you understand their purpose.

You can manually add a data silo at any time by clicking on the "Add Data Silo" button.

The name and, where possible, an automatically-loaded logo of the data silo in your inventory. Any data silos added to your Data Inventory will also appear in Integrations and vice versa. Any changes made in Data Inventory will also be reflected in Integrations.

The person who is responsible for managing this data silo in your organization. Setting the Owner for a Data Silo here will be reflected everywhere in Transcend.

The total number of datapoints housed in this data silo. Clicking on this field will show you the filtered list of datapoints associated with this data silo in the Datapoints tab.

Which categories of individuals have personal data in this system. An example of a data subject might be "Employee" or "Customer".

A summary of the purpose of this data silo. This is typically pre-populated by Transcend- but you can overwrite it if need be.

The Datapoints tab gives you a detailed view of every piece of data your systems house across your company's digital footprint.

The data inventory view within Transcend Data Mapping

The system that a datapoint belongs to. Read more about Data Silos.

The name of a given datapoint. This is associated with the literal name of an object inside a system. Read more about Datapoints.

For systems with customizable schema, such as a database or Salesforce, "Key" represents the property of an object. For example, in a relational database, "Key" corresponds to a column name, and in Salesforce, a field in a Salesforce Object.

Here you can choose the category that best describes the datapoint. This describes what type of data is contained here (e.g., credit card numbers would have the Financial data category). This is typically pre-populated by Transcend (either through an ML classifier or our pre-labeled dataset for common tools). Feel free to override our labels if your use case needs customization. Any categorizations you make here will be used to help automatically generate your ROPA.

Here, you can choose the purpose that best describes why your company uses this data. This describes why you collect this data (e.g., Contact information in Mailchimp is likely used for Marketing purposes). This is typically pre-populated by Transcend (either through an ML classifier or our pre-labeled dataset for common tools). Feel free to override our labels if your use case needs customization. Any categorizations you make here will be used to help automatically generate your ROPA.

This field is used to help describe what this datapoint is and how it's used. This also comes pre-labeled for the most common tools, and you can edit any datapoint's description.

The Data Categories tab is a great way to see the breakdown of how many datapoints you have in each category. Clicking the datapoint count on a category will link you to a filtered list of all the datapoints belonging to that category.

The Purposes of Processing tab is similar to the Data Categories tab in that all purposes of processing are counted across all your datapoints. Similarly, you can click on the datapoint count for any purpose of processing to see a filtered list of all datapoints that are used for that purpose.

The Datapoints tab in Data Inventory can be filtered by Data Silo, Data Category, and Purpose of Processing. Click the filter button in the top-right corner of the Datapoints tab to get started.

The filter button in the data inventory.

You can export a CSV from any table in Data Inventory. Any filters applied to the table will also apply to your export. You can also use our GraphQL API to access your Data Inventory programmatically.

Export to CSV button in the data inventory.