The phenomenon of data becoming dormant is not quite as true for structured online
data.
There are certain types of business where the phenomenon of data aging is not as true, as
well. One type of industry is the life insurance industry, where actuaries are regularly
looking at data that are over 100 years old. And in certain scientific and manufacturing
research organizations, there may be great interest in results that were generated over 50
years ago. But most organizations do not have an actuary or a scientific research facility.
For those more ordinary organizations, the focus is almost always on the most current
data.
The declining curve of usefulness can be expressed by a curve, as seen in Fig. 1.6.5.
Fig. 1.6.5 The declining curve of usefulness of data.The declining curve of usefulness states that over time, the value of data decreases, at
least insofar as the probability of access is concerned. Note that the value never actually
gets to zero. But after a while, the value nearly approaches zero. At some point in time,
the value is so low that for all practical purposes, it might as well be zero.
The curve is a rather sharp curve—a classical Poisson distribution.
An interesting aspect of the curve is that the curve is actually different for summary and
detailed data. Fig. 1.6.6 shows the difference in the curve for detailed data and summary
data.
Chapter 1.6: The Life Cycle of Data: Understanding Data Over Time