Data retention refers to the storage of a system's information for a specified period of time. This information should be examined according to the different data domains (e.g., transactional, consumer, product, complaints, etc...) Each domain may have separate retention requirements. For example, information on products and transactions may be stored indefinitely, however, consumer records maybe be purged after 4 years of inactivity.
Considerations for data retention include:
- System - What are the uses of the information? Will you be doing long-term trend analyses or operational reporting only?
- Legislative Restrictions - Some information sets may have legislation concerning their mandatory disposal after a specified elapsed time. Other places have legislation mandating data retention for specific industries (e.g., Europe has legislation mandating data retention for telecommunications firms as part of their anti-terrorist activities.)
- Useful Life - How old can information get before it becomes dated? For example, marketing information that is 12 years old probably has little value to marketers. Because you were a student 12 years ago probably does not help a marketer that much now.
- Customer Service - How much historical information on a client is required to deliver appropriate levels of service?
- Data Aggregation - Should old information that is being disposed of be rolled-up so that long-term trend reporting can take place? Do you ever anticipate looking at the detailed information again?
- Data Disposal - Should old information be kept offline or removed permanently? What type of archiving is necessary?
Based on your needs, your data retention strategy may require additional capacity and storage facilities. All of this comes at a price. As such, you must be careful to balance your desire to retain data with the cost of its maintenance.