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Data Life-Cycle Management: More than a cost saving exercise.

So much has been said and written, and will continue to be, about the important role access to reliable, consistent, accurate and timely information play within an organisation. However, despite the obvious pitfall, inadequate attention is often paid to managing data that no longer provide value. One need look no further than the costs associated with managing redundant data in operational applications to understand the importance.

Generally, information become obsolete over time. In addition, so does the data that produces it. Subsequently, the accuracy of the information provided diminishes. This could affect decision-making within an organisation. Ultimately, leading to unreliability. Throw in the operational costs associated with maintaining the redundant data and you have a real problem at hand.

Tackling this ever-changing phenomenon is a challenge. As a result, questions such as the following come to the fore. Who decides when data has outlived its usefulness? How long should data be stored? How do organisations handle data that is no longer used?

Perhaps, the answers lie in data governance. We opine that data governance, which in itself should be underpinned by a data governance charter, should govern the life cycle of Information within an organisation. Click on this link for more information on a practical approach to data governance.

Considering the huge amount of data generated by organisations, and the questions posed earlier in this article, the challenges of managing the lifecycle of data are all to obvious. Nevertheless, these are challenges that should be addressed. For this purpose, there are applications in the market designed to deal with the burgeoning amount of redundant data. Some have the capability to address archiving of data in legacy applications and archiving redundant data in ‘live’ applications. Practically, these applications go a long way to address some of the technical issues surrounding information life-cycle management. However, investing in software without sound data governance policies posses a great risk, which should be avoided.

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