Use cases

Data Minimization

Reduce risk, storage costs, and meet regulatory requirements by deleting your over-retained data

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Defensible Data Disposal

Leverage our powerful workflows to identify and remediate redundant, obsolete, and trivial data

Comply with privacy regulations

Remove over-retained data to facilitate compliance with evolving privacy regulations and align with future laws

Reduce your DSAR surface area

With a smaller data footprint you can respond quickly to data subject access requests (DSARs)

Lower your risk exposure

Reduce your exposure to judicial and regulatory fines in the event of a data breach

Optimize storage costs

Lower your storage costs and free up valuable resources by disposing of excess records

Find the information you need

Improve the findability of information for your employees as they won't need to search through outdated content

Improve customer trust

By handling you customer’s data responsibly they are more likely to put their trust in your brand

Bigger is not better when it comes to personal data. Companies that put data minimization practices in place are better positioned to meet the challenges of today’s regulatory environment.

What is data minimization?

Data minimization means limiting the amount of personal data collected to only what is needed for a specific purpose and retained only for as long as necessary or as required by law.
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Does data minimization appear in privacy laws?

Yes, there are several laws that mention this principle. In the EU’s General Data Protection Regulation (GDPR), data minimization is a named principle, Article 5. In the US, the HIPPA Minimum Necessary Rule states “A covered entity must make reasonable efforts to limit the scope of the PHI it uses, discloses or requests to the minimum necessary to accomplish the intended purpose of the use, disclosure, or request.” The Brazilian General Data Protection Law (LGPD) also sets forth the need for data minimization. While other regulations like the California Consumer Privacy Act (CCPA) don’t state minimization directly, they include similar concepts around collection limitation.
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How can we build data minimization into our business processes?

Minimization concepts should be built in during the earliest phases of a data accumulation program. You should always consider why your organization might retain any category of content in the first place, and then build your processes around that.
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Is this defensible?

Yes! The workflows are defensibly documented. We have domestic and international retention rules for records.
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Don’t see a position that’s the right fit for you?

We’re always keen to meet people who’d like to join our team. To be considered for future positions, please send your resume or CV to careers@activenav.com.

“We generate a huge volume of unstructured data and growth rates are expanding significantly. We are now incorporating the software as a primary mechanism for file analysis and disposition. We see a strong ongoing business case with this solution by lowering our storage costs while strengthening our overall information governance across Rio Tinto.”