This PIG – Predictive Information Governance – Is Starting to Fly

As the name implies, unsupervised machine learning – computers teaching themselves – removes the human factor. And once the error rates are low enough, truly automated predictive information governance is realized. The system can now automatically collect, categorize, store, protect, safeguard access, and apply retention/disposal rules.

Extract from article by Bill Tolson

Today, even the largest and most sophisticated organizations are still trying to hone (i.e., wrap their arms around) their information governance policies.  And however cliché it is to say it, every organization – private, public, government, for-profit, or non-profit is facing an exponential explosion of data.  The idea that end users alone (with a bit of software support) would be responsible for seeing that information governance policies are adhered to is neither realistic nor practical.

Given the potentially severe consequences of not doing so, most organizations have focused on perfecting regulatory and legal records management.  But that data typically accounts for just 6-10 percent of an organization’s overall data.  That leaves quite a bit of data in the hands of individual users to manage.  And if we are being realistic here, that really means the majority of an organization’s data is not being managed at all (sticking it in a folder on your desktop, or in an email folder does not qualify as “management”).

The Holy Grail for information governance has become error-free, intelligent, automation that removes end users from the process.

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