Boldon James. Data Classification as a Catalyst for Data Retention and Archiving

Businesses manage data retention in a multitude of ways for many different reasons, ranging from technical considerations to privacy and liability concerns. The regular considerations are, and will always be, top of mind to include regulatory requirements and compliance, financial reporting, disaster recovery and others – but there is a growing sense if not mandate to collect and retain only the data necessary and to keep it for the minimum amount of time required to successfully complete the task at hand.

While many organizations have data governance policies in place that define data classification and retention schemes, many do not express those policies in language that facilitates the efficient and effective retention activities that are available to their enterprise. Similarly data destruction activities need to be clearly defined to support the growing practice of destroying the data whose retention is no longer mandated by regulation and that no longer provides value to the business. The direct and indirect cost of retaining data beyond its useful life, coupled with the potential liability that it represents, quickly becomes burdensome, certainly as data is generated at an ever increasing rate.

The variability in business drivers, data governance policy socialization, acceptance and its application can lead to conflicting and confusing archiving practices. By involving users in the classification of their data it’s possible to alleviate the need for subjective policy interpretation and ad-hoc application of data retention and archiving practices. By assigning value to information through classification metadata, retention policies can be enforced automatically allowing third party archiving systems the ability to make your data archiving and retention capabilities more efficient, reliable and precise.

Some benefits of managing data retention, archiving and subsequent destruction include but are not limited to:

• Increased consistency with automatic application of data retention policies
• Reduced cost of data storage
• Increased operational efficiency & effectiveness
• Improved data reliability improves performance of eDiscovery
• Supports compliance obligations for data retention and disposal
• Makes user-driven classification easy
• Increases awareness of data value and sensitivity
• Improved compliance with industry regulations

Many companies are finding it difficult to rationalize their assigning value to data but in turn not managing them as they would any other valuable asset with a traditional life cycle approach. The recognition and similarly the capability to accurately assign data retention characteristics is an achievable albeit critical component of corporate data hygiene and a contributing factor to regulatory compliance that should not be overlooked.

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