By David Loshin
· Few or no well-defined processes for evaluating the severity or root causes of data issues
· Little or no coordination among those investigating data errors
· Evaluating the same issues multiple times
· Correcting the same errors multiple times
These are all manifestations of a more insidious problem: knee-jerk reactivity,
which presumes that addressing the symptoms solves the problem. But in reality,
applying these bandages to open wounds is merely a temporary fix. This suggests
that incremental maturation of data quality processes involves transitioning
from a reactive environment to one that operates within the context of a series
of policies and controls.
The manifestations of immaturity listed here are some fertile areas for improvement, namely:
· Defining processes for evaluating data errors when they are identified
· Instituting methods for coordinating those evaluations
· Applying corrections once, and only once.
As a byproduct of coordinating evaluation, your team will be less inclined to
evaluate the same issues multiple times! In my next set of posts, we will look
at ideas for each of these suggestions.