Overview#

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This is way too complex to understand. Basically, once data Discovery has been performed and a Data Policy developed, then Data Management is the data Life cycle

Information Lifecycle Management (ILM) is the life cycle for data that consists of the policies, processes, practices, and tools used to align the business value of data with the most appropriate and cost effective Information Technology architecture from the time of data creation through disposition.[1]

This is way too complex to understand. Basically, once data Discovery has been performed and a Data Policy developed, then Data Management is the data Life cycle

Information Lifecycle Management Policy[2]#

Information Lifecycle Management policy consists of the overarching storage and information policies that drive management processes. Policies are dictated by business goals and drivers. Therefore, policies generally tie into a framework of overall IT governance and management:

Information Lifecycle Management Operational[2]#

Operational aspects of Information Lifecycle Management include and day-to-day processes and procedures necessary to manage a data architecture.

Information Lifecycle Management Infrastructure[2]#

Infrastructure facets of ILM include the:
  • logical and physical architectures
  • applications dependent upon the storage platforms
  • Data Protection of storage
  • data center constraints.
Within the application realm, the relationship between applications and the production, test, and development requirements are generally most relevant for ILM.

Information Lifecycle Management Functionality[2]#

For the purposes of business records, there are five phases identified as being part of the Information Lifecycle Management continuum along with one exception. These are:

More Information#

There might be more information for this subject on one of the following:
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop