What is data minimization?

Data minimization is a data privacy practice that collects and uses the least amount of data possible to serve a specific purpose. Minimization improves data privacy and is a key component of regulations such as the European Union’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and Brazil's General Personal Data Protection Law (LGPD).

Minimization relies on three principles:

Data should only be collected with the individual's express consent. This consent must be clear and informed—organizations should specify what data is collected, how it will be used, and when it will be deleted.

Only data required for the stated purpose should be collected. For example, an organization conducting demographic analysis might collect data such as user location, age range, and purchase history. Other data, such as names, phone numbers, or birthdates, aren't required for this purpose and shouldn't be collected.

Once data has been analyzed and applied, it should be deleted. User consent agreements should specify how long data will be held during and after use. If organizations want to reuse data for a similar purpose, they must gain new consent.

Applying data minimization offers benefits, such as the following:

The more data an organization collects and stores, the greater the potential loss. By collecting and using only the information required to achieve a specific goal, organizations can potentially reduce the impact of a security breach.

Storage costs money. Data minimization reduces the amount of data stored and helps control storage costs.

Data minimization is now commonplace in privacy legislation. By adopting this practice at scale, organizations can stay ahead of regulatory expectations.