DARK DATA: WHAT IT IS AND WHY IT NEED NOT BE SO DARK AFTER ALL
There is an ominous ring to the word ‘dark’. The words dark web, dark matter, and dark night, to name just a few, evoke feelings of fear and anxiety.
Dark data is no different.
Getting its name from its invisible nature, dark data is being increasingly considered a problem in the making for organizations. Gartner?(1)?defines it as ‘the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).’
Dark data is therefore information that organizations collect and store, advertently or inadvertently, but hardly ever use, process, or analyze. More often than not this data is unstructured and unrefined. Most organizations are in the dark as to what, where, and how much of this data they have on the cloud and on-prem.
Types of Dark Data
In essence, any data that is generated and stored has the potential to become dark data, if it is not used. The internet is however the biggest contributor to the volume of dark data, simply because of the staggering amount of data that is created at any point. In a simple case of a social media post, dark data can be created around user logins, edits, images, geo-locations, tags, users, likes, comments, and more!
In an organization, dark data can comprise all and more of the items as mentioned below:
Alarming Proportions
Logikcull quotes the IDC?(3)?estimates of dark data as being 90 to 95% of all data, with a strong likelihood of it growing to 97% with a CAGR of 23%. When one considers that this data often lies idle and unutilized, one realizes the enormous cost of maintenance, let alone the security risk that it involves.
Gartner?(4)?had already sounded the alarm bells, estimating that 80% of organizations in 2021 would fail to develop a consolidated data security policy across silos, leading to potential noncompliance, security breaches, and financial liabilities.
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The Challenges
Because it contains so much information about the organization, dark data can pose significant risks.
The Bright Side
Despite the apparent danger and potential for misuse, there is a bright side to dark data as well. Organizations would do well to remember that this dark data, despite its state, is still ‘proprietary data’ and still has value, if handled effectively. The advent of Machine Learning (ML) and Artificial Intelligence?(5)?offer viable solutions for the humungous task of handling dark data. AI in particular can provide useful insights into the seemingly-bottomless lake of data an organization may have. While there may be considerable costs of investment involved, the investment is well worth it considering the benefits.
The benefits that could accrue include:
Final Thoughts
A good thing for organizations to remember when dealing with dark data would be that, despite its volume, unrefined state, obvious risks, and maintenance costs, it need not be so dark after all. Though comparisons can be odious, a good analogy could be that every dark cloud has a silver lining and after the dark, unfailingly comes the light.
Click?Here?to know more about the integrative cloud security solutions that Aurora has to offer through?CloudCodes. For a more comprehensive understanding of our cybersecurity services reach us at?[email protected]?or call +1 888 282 0696
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2 年Interesting! Never thought of data in this manner.