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ROT can place drains on storage capacity, and create difficulties for search and retrieval, but the problems can be much more serious. Retaining ROT can be risky and expose the business to regulatory and legal violations.
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Organizations need to balance Data Privacy with Records Management, or enhance Records Management with Data Privacy, if you prefer. To do this, they need clear policies, focused processes, applicable and performant tools, and possibly even consultative help.
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Structured data is generally created to make it easy to access, search, analyze, and process by computers for computational purposes and can be difficult, voluminous, and complex for people to try and search or utilize directly, let alone govern.
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Much of what is being stored can be considered ROT, or redundant, obsolete, or trivial data, aka junk. ROT overburdens your storage systems, but there are other risks, such as compliance issues, security threats, and high costs.
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There is no question that much of this enterprise information is of questionable value, particularly since significant portions of it are old, unused, or duplicative, what we commonly call “ROT”. What is the true impact of having so much data, so much ROT, in our companies?
The Gartner Glossary defines digital business transformation as the process of exploiting digital technologies and supporting capabilities…
The Gartner Glossary defines digital business transformation as the process of exploiting digital technologies and supporting capabilities…
The Gartner Glossary defines digital business transformation as the process of exploiting digital technologies and supporting capabilities…
The Gartner Glossary defines digital business transformation as the process of exploiting digital technologies and supporting capabilities…
Data Classification is a fundamental aspect of managing information within an organization. By classifying data, you gain greater control over your information, leading to improved data security, compliance, and operational efficiency.
Data minimization is the reduction and removal of data that no longer serves its stated business purpose. Data minimization is one of the most important practices your organization can follow to properly manage personal data – and comply with global privacy laws.
To help demonstrate good (and bad) practices regarding data minimization, we’ve gathered up a few real-world examples for you to consider.
