Dark Data is information that an organization collects, stores, or processes, but never analyzes, reuses, or leverages. It takes up storage space, poses a security risk, and in many cases violates the GDPR minimization requirement.
What is Dark Data?
Gartner estimates that more than 80% of the data organizations generate is unstructured and largely unused. A large portion qualifies as Dark Data: files that were once stored but have never been viewed or used again.
Examples are everywhere: email attachments from projects completed years ago, duplicate versions of contracts sitting somewhere on a shared drive, logs from business systems that no one reads, scanned forms that were never indexed. All these files consume storage space, increase your attack surface in the event of a data breach, and pose a GDPR risk if they contain personal data.
M-Files solves the Dark Data problem by making all information findable and classifiable through metadata, and by setting up automatic retention rules that archive or delete documents in a timely manner.
Risks of Dark Data
How do you tackle Dark Data with M-Files?
Frequently Asked Questions about Dark Data
Dark Data is information that an organization collects but never analyzes or utilizes.
Examples include old email attachments, outdated files, and forgotten scans that take up storage space.
Dark Data contains sensitive information that is no longer needed but is still kept.
In the event of a data breach, forgotten files are also exposed. It also violates the GDPR minimization requirement.
Gartner estimates that 80% of the data organizations collect is unstructured and largely unused.
A large part of this qualifies as Dark Data.
M-Files makes all data findable through metadata and offers automatic retention rules that archive or delete documents in a timely manner.
Dark Data is structurally reduced.
GDPR requires data minimization.
Keeping personal data longer than necessary violates this principle.
Automatic retention rules in M-Files are the most effective measure.