Data life cycle management (DLM) is a policy-based approach to managing the flow of an information system's data throughout its life cycle: from creation and initial storage to the time when it becomes obsolete and is deleted. DLM products automate the processes involved, typically organizing data into separate tiers according to specified policies, and automating data migration from one tier to another based on those criteria. As a rule, newer data, and data that must be accessed more frequently, is stored on faster, but more expensive storage media, while less critical data is stored on cheaper, but slower media.
Hierarchical storage management (HSM) is one type of DLM product. The hierarchy represents different types of storage media, such as RAID (redundant array of independent disks) systems, optical storage, or tape, each type representing a different level of cost and speed of retrieval when access is needed. Using an HSM product, an administrator can establish and state guidelines for how often different kinds of files are to be copied to a backup storage device. Once the guideline has been set up, the HSM software manages everything automatically. Typically, HSM applications migrate data based on the length of time elapsed since it was last accessed, while DLM applications enable policies based on more complex criteria.Content Continues Below
The terms data life cycle management and information life cycle management (ILM) are sometimes used interchangeably. However, a distinction can be made between the two. According to Karen Dutch, vice-president of product management at Fujitsu Softek, DLM products deal with general attributes of files, such as their type, size, and age; ILM products have more complex capabilities. For example, a DLM product would allow you to search stored data for a certain file type of a certain age, for example, while an ILM product would let you search various types of stored files for instances of a specific piece of data, such as a customer number.
Data management has become increasingly important as businesses face compliance Sarbanes-Oxley Act, that regulates how organizations must deal with particular types of data. Data management experts stress that data life cycle management is not a product, but a comprehensive approach to managing an organization's data, involving procedures and practices as well as applications.