Because modern privacy is still young, the world doesn’t yet have a shared understanding of every term in privacy compliance. To help bring us to that shared understanding, here’s our primer on what we mean when we say “automated data mapping.”
Defining Automated Data Mapping
Automated data mapping is about more than just one visual snapshot of your data flows. It’s about how you get to that visual map and what you do once you have it. To create a data map, you need a platform that can efficiently inventory diverse data formats across your tech stack. And once you have your data map, you need a platform that can make sense of the data and deliver the reports needed to meet privacy compliance.
Automation is key to both creating a data map and making sense of the map once it is built. When we talk about automated data mapping, we are talking about automated data management and inventory tools that build on the basic legal information you provide. The result is an automated platform does the heavy lifting for you, giving your team and users a seamless experience when users exercise their data rights.
Regardless of your background, we’ll walk you through the role of automation in data mapping.
Making Sense of Schemas
Put simply, a schema is a complete layout of a database: what it stores and how it stores that information. When you add a SaaS app to your company’s tech stack, you want to know what kind of personal information the app gathers. Having already analyzed this app’s schema, an automated tool pre-fills the types of information likely to reside in this app’s systems. This brings a huge time savings to your team, who’d otherwise need to contact the app’s engineers to gather this insight.
Harmonizing Data Structures
Sometimes, the same piece of information is stored in different formats or data structures. For instance, one app might store each customer’s name in one string of characters, like “John Smith.” Meanwhile, another app stores first and last names in separate strings: one for “John” and another for “Smith.”
When John Smith, a hypothetical California resident, asks to access all personal data you have on him, you might only see some of his data when conducting a basic search for “John Smith” in your systems. This one oversight can cost you hundreds in CCPA fines, not to mention the cost in users’ trust.
Automated data mapping detects and reconciles different data structures to deliver an accurate view of your systems.
Updating Systems Automatically
Suppose John Smith requests that you delete all of the information you hold about him. It’s on your company to enforce that deletion across every part of your company’s data flow, including third parties’ systems. Here’s where automation does the heavy lifting. An automated data mapping tool connects disparate databases to seamlessly enforce such a request.
Generating Useful Reports
With Ethyca, a data map distills your company’s complex data flows into a clear visual. You also receive an automatic and downloadable report that meets GDPR requirements for a Record of Processing Activities (RoPA). This report simplifies internal and external review while remaining ready to adapt to changes in your tech stack. Below is a simple example of what you’d expect to find in a RoPA. Ethyca’s is considerably more robust!
Seeing Data Mapping in Action
More than a static visual, a data map is an evolving project to account for all data in your systems. Now that you understand data mapping, you probably want to see it in action. Drop us a line, and we’ll gladly show you what data mapping can bring to your business.