Data Life Cycle Management

Evolution of Data in Enterprises

By Hari Mailvaganam

Data becomes active as soon as it is of interest to an organization. Data life cycle begins with a business need for acquiring data. Active data are referenced on a regular basis during day-to-day business operations. Over time, this data loses its importance and is accessed less often, gradually losing its business value, and ending with its archival or disposal.
Data Life Cycle
Figure 1. Data Life Cycle in Enterprises
Active Data

Active data is of business use to an organization. The ease of access for business users to active data is an absolute necessity in order to run an efficient business. 

The simple, but critical principle, that all data moves through life-cycle stages is key to improving data management. By understanding how data is used and how long it must be retained, companies can develop a strategy to map usage patterns to the optimal storage media, thereby minimizing the total cost of storing data over its life cycle.

The same principles apply when data is stored in a relational database, although the challenge of managing and storing relational data is compounded by complexities inherent in data relationships. Relational databases are a major consumer of storage and are also among the most difficult to manage because they are accessed on a regular basis. Without the ability to manage relational data effectively, relative to its use and storage requirements, runaway database growth will result in increased operational costs, poor performance, and limited availability for the applications that rely on these databases. The ideal solution is to manage data stored in relational databases as part of an overall enterprise data management solution.

Inactive Data
 
Data are put out to pasture once they are no longer active. i.e. there are no longer needed for critical business tasks or analysis.
 
Prior to the mid-nineties, most enterprises achieved data  in Microfilms and tape back-ups.
 
There are now technologies for data archival such as Storage Area Networks (SAN), Network Attached Storage (NAS) and Hierarchical Storage Management. These storage systems can maintain referential integrity and business context.
 
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