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Discovering Dark Data - An Elusive Security & Privacy Risk in the Cloud

In this infographic, you will learn about:

  • How to detect shadow and native data assets residing across multi-cloud environments and extract them into an asset catalog with mapping/tagging of the data inside each system.
  • How organizations can detect risk, detect sensitive data residing in structured and unstructured systems, map personal data to the right owner, and ensure privacy obligations with the help of automation.

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A significant amount of "Dark Data" escapes detection because of the exponential growth of unstructured data systems. Data that isn’t controlled and mapped has a higher likelihood of violating privacy laws.

With the widespread adoption of multi-cloud frameworks, businesses frequently have little to no visibility into the data stored on these clouds, despite the growing trend. Download the infographic to learn how to discover dark data and ensure swift compliance.

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Our Readers Frequently Ask:

Dark data discovery is the information assets businesses acquire, process, and retain during routine business activities but often fail to employ for other purposes.

Dark data is all of an organization's unused, undiscovered, and untapped data. It includes anything from machine data to server log files to unstructured data collected from social media. Dark data is produced due to consumers' daily online interactions with numerous devices and systems. Examples of regularly used company data include names, addresses, phone numbers, and identification numbers.

In a typical organization and shared storage environment, between 60 and 85 percent of unstructured data is dark. These are documents that belonged to a former employee of the business; no one has accessed them in years.

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