Classifying data is becoming a critical IT activity for the purposes of implementing the optimal data solution to store, tier and protect data throughout its lifetime. Developing a data classification methodology for a business involves establishing criteria for classes of data or application based on its value to the business. Four distinct levels of classifying data or applications are commonly used:

• Mission-critical
• Vital data
• Sensitive
• Non-critical

Determining these levels takes some cooperative effort within the business and when completed, enables the most cost-effective storage and data protection solutions to be implemented. Data classification levels also identify which backup and recovery or business resumption solution is best suited for each level to meet the RPO (Recovery Point Objective) and RTO (Recovery Time Objective) requirements. While very important, RTO & RPO are not the only parameters used to classify data. Other considerations include availability, length of data retention, service levels and performance requirements, and overall costs. The figure below illustrates an effective data classification model.

Defining and communicating these levels is a first step to tiered storage success.