Organizations using analytics or artificial intelligence/machine learning applications for business intelligence or to monetize data should first reckon with their “dark data,” say experts at Aparavi, the company behind the award-winning Aparavi Data Intelligence and Automation Platform.
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“Gain understanding and visibility into dark data as a first step to leveraging it; otherwise, you will continue to grossly misspend resources holding onto information that isn’t being put to work for the good of the business. An automated platform like Aparavi’s can sift through data in seconds.”
More than half of business data on average is “dark data:” information that is unknown, unused—and untapped for value. Gartner notes that businesses may keep dark data out of compliance fears, and says retaining and securing dark data can incur more expense and risk than reward.
Aparavi recommends the following tactics to identify, exploit and utilize dark data:
Shed some light
There’s no way around it: it takes a lot of searching to find what’s in the dark. Use automated search tools to reveal all files in the system, including cloud, remote, and on-premise resources. A deep scan will uncover information you didn’t know you had.
Play cleanup
There’s a reason data goes dark: much of it is redundant, obsolete, or trivial (ROT). Redundant files such as autosaves and temporary files can be deleted outright, as can duplicate files. Trivial data often includes personal files employees stash on company machines, which should be dumped. On the other hand, outdated files may help you identify trends and guide future decisions.
Get organized
Finding and deleting unneeded data will help contain storage spending, but classification and tagging will go further towards reaping business value. Once files are out of the dark, use data management tools to identify files by content or keywords, date last accessed, creator, or other appropriate criteria so they are easy to call up for analytics and AI/ML applications.
Banish the darkness
From this point onward, keep a better handle on files with regular search, discovery, and classification, before data goes dark. Set and automate policies so files are managed and stored according to the business need; for example, automatically delete data that isn’t potentially useful for analytics when retention periods expire (if a regulation says to keep certain files for six years, destroy after six years and one day).
Drill into data
With your files organized and tagged, and ROT data removed, you have a higher-quality data set and can select the right files for analysis by business intelligence tools. A smaller volume of quality data will yield more actionable results—faster.
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“Most organizations don’t know the importance or value of their information, and if you don’t know what you have, you can’t effectively capture, categorize, analyze, use, and reuse information,” said Adrian Knapp, CEO and founder of Aparavi. “Gain understanding and visibility into dark data as a first step to leveraging it; otherwise, you will continue to grossly misspend resources holding onto information that isn’t being put to work for the good of the business. An automated platform like Aparavi’s can sift through data in seconds.”
Aparavi’s data intelligence and automation platform addresses dark data by giving managers insight into data by location, owner, content/keyword, creation, last access, extension type, and dozens of other criteria. By presenting a “big picture” of data, wherever it resides, organizations can take meaningful action to safeguard sensitive files; eliminate ROT data; and automatically apply governance rules such as move to cloud/offsite storage or delete when retention periods expire, which often reduces the on-premises storage footprint by as much as 40 percent.
Aparavi empowers organizations to find and unlock the value of their data, mitigate risks, and reduce storage requirements and costs, but also transform data into a competitive asset that is more accessible for data analytics, machine learning and other tasks
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