Data classification emerging as an essential business/IT practice

Corporate information resources regularly stretch into the terabytes (thousands of gigabytes) with many thousands (even millions) of individual files to contend with -- but the problem is now far more complex than simply "finding files". Finding specific files among this confusing hodgepodge of information is inefficient and frequently incomplete. Companies often fail to recognize the importance of their data and its impact on everyday business operations. The process of "data classification" attempts to fill this void by helping businesses understand what data is actually available, its location in the enterprise, how that data is being accessed and how it must be protected to meet legal and regulatory requirements.

Corporate information resources regularly stretch into the terabytes (thousands of gigabytes) with many thousands...

(even millions) of individual files to contend with – but the problem is now far more complex than simply "finding files." Finding specific files among this confusing hodgepodge of information is inefficient and frequently incomplete. Companies often fail to recognize the importance of their data and its impact on everyday business operations. The process of "data classification" attempts to fill this void by helping businesses to understand what data is actually available, its location in the enterprise, how that data is being accessed, and how it must be protected to meet legal and regulatory requirements. Of course, data classification is not a simple or intuitive process. It requires a careful evaluation of data against a broad range of business needs (along with complex legal and compliance issues), and the process can become complex for large organizations. But once data classification is accomplished, a corporation will be well on the way to successful implementation of information lifecycle management. The following article outlines essential data classification concepts, offers vendor and user insights into enterprise applications, and examines the future of this practice.

Go to the next part of this article: Data Classification: An overview

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  • Introduction
  • Data classification: An overview
  • Data classification: Strengths and weaknesses
  • Data classification: The vendors
  • Data classification: User perspectives
  • Data classification: Future directions
  • Dig Deeper on Data storage compliance and archiving

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