Information life cycle management (ILM) is the inclusive management approach of the flow of an information system’s data from the time it is created and in the initial storage stages to the time it becomes of no use or deleted. ILM facilitates for a more sophisticated storage management criterion. This data management approach allows new and frequently accessed data to be stored faster though in a slower device. In the storage industry, ILM has proven to be the catchphrase. This is because of the implementation of the new rules, regulations and other strategies for recovering disaster that face stored information.
These rules and data recovery methodologies have greatly assisted the information technology (IT) professionals experience the minimum management difficulties and also adhere, to the latter, the earlier stated new standards of the ILM approach. Since operations managers are concerned with the ways and procedures in which data is used while the IT managers deal with the storage and maintenance of these data, more often than not, differences arise between them. In remedying this, ILM has played a vital role in building a technological rapport between these personnel.
ILM is capable of achieving this through its ability to combine various processes and technologies which are the major determinants of the flow of data via the network environment. These technologies include assessment, classification, socialization, review and automation (Duplessie, Marrone, Kenniston, 2003). During the assessment phase, the IT managers are in a position to utilize the storage resource management (SRM) mechanisms in their efforts to determine what data is stored where within their storage devices.
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Reports from the SRM tools help the IT managers understand the data usage prototypes by the operations managers thus easing their task to defragment the storage device appropriately for maximum utilization and also cut down the cost implications associated. Operations managers are the in-charges of the data usage in the various departments and are obliged to report the patterns of the data usage and the criticality of these data to the IT managers.
This helps the IT personnel to prioritize the data on the basis of the prerequisites of the business hence creating a good social understanding between these managers. At this socialization stage, both the IT and the operations managers work together to classify the data on the bases of type, age, organization and value (Duplessie, Marrone, Kenniston, 2003). The IT department will therefore have been aided to rationally establish the ILM policies and standards.
Moreover, this managers’ collaboration avoids files duplications, excess capacities in either department or even the existed of unnecessary file in the storage devices. Classified data helps in determining the storage location and also eases its retrieval thus fostering the data automation process. Based on the users defined data retrieval policies, automation through Automated Data Migration (ADM) tools facilitates the transfers of data from one storage location to another and also from one user to the other.
This process saves storage and data migration costs by optimizing the resources for storage according to the data value. Additionally, automation boosts data disaster recovery thus ensuring the continuity of the business (Duplessie, Marrone, Kenniston, 2003). Therefore in conclusion, ILM gives remedies to pressing organizational challenges such as ineffective utilization of the storage devices, the cost implications of the storage, disaster recovery and the management of the storage to avoid data replications.
Since these are the conflict grounds for the IT and the operations managers, once solved makes these officials to be at peace and run the business smoothly.
Duplessie, S. , Marrone, N. & Kenniston, S. (2003). The New Buzzwords: Information Lifecycle Management.
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