Information Life Cycle Management (ILM)

Information life cycle management (ILM) is a comprehensive approach to managing the flow of an information system’s data and associated metadata from creation and initial storage to the time when it becomes obsolete and is deleted. Unlike earlier approaches to data storage management, ILM involves all aspects of dealing with data, starting with user practices, rather than just automating storage procedures, as for example, hierarchical storage management (HSM) does. Also in contrast to older systems, ILM enables more complex criteria for storage management than data age and frequency of access.

ILM 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. However, the ILM approach recognizes that the importance of any data does not rely solely on its age or how often it’s accessed. Users can specify different policies for data that declines in value at different rates or that retains its value throughout its life span. A path management application, either as a component of ILM software or working in conjunction with it, makes it possible to retrieve any data stored by keeping track of where everything is in the storage cycle.

ILM is often considered a more complex subset of data life cycle management (DLM). 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 issues in the wake of legislation, such as HIPAA and the Sarbanes-Oxley Act, that regulates how organizations must deal with particular types of data. Data management experts stress that information life cycle management should be an organization-wide enterprise, involving procedures and practices as well as applications.