The Picture of Dorian Gray was a 19th century novel written by Oscar Wilde, which told the story of a young man who sold his soul to remain forever young and beautiful by having his recently painted portrait age rather than himself. One of the allegories that can be drawn from the novel is our desire to cling,
The Picture of Dorian Gray was a 19th century novel written by Oscar Wilde, which told the story of a young man who sold his soul to remain forever young and beautiful by having his recently painted portrait age rather than himself. One of the allegories that can be drawn from the novel is our desire to cling, like Dorian Gray, to an idealized image of ourselves and of our lives.
I have previously blogged that when an organization’s data quality is discussed, it is very common to encounter data denial.
This is an understandable self-defense mechanism from the people responsible for business processes, technology, and data because of the simple fact that nobody likes to be blamed (or feel blamed) for causing or failing to fix data quality problems.
But data denial can also doom a data quality improvement initiative from the very beginning.
Of course, everyone will agree that ensuring high quality data is being used to make critical daily business decisions is vitally important to corporate success. However, for an organization to improve its data quality, it has to admit that some of its business decisions are mistakes being made based on poor quality data.
But the organization has a desire to cling to an idealized image of its data and its data-driven business decisions, to treat its poor data quality the same way as Dorian Gray treated his portrait—by refusing to look at it.
However, The Data Quality of Dorian Gray is also a story that can only end in tragedy.
