This post is inspired by a little tweet chat I had with Daragh O Brien this morning:
The data quality angle was that a simple data quality rule around age (or date of birth) for living persons would be a check creating a warning if age is above 122, because this would, if true, be a new entry in the book of records.
Jeanne Louise Calment of France had the longest confirmed human life of span being 122 years.
Your data quality age check may even be refined as the record for a male is 115 years.
Christian Mortensen, born in Denmark and deceased in the United States, holds that record.
Both Jeanne Calment and Christian Mortensen have shared their secret behind a long life.
Surprisingly both recipes include what is usually not considered good for your health.
Jeanne Calment recommended a diet of port wine and she ate nearly one kilogram of chocolate every week.
Christian Mortensen on the other hand recommended lots of good water and no alcohol – but then a good cigar.
Even though there are lots of recipes and examples out there for a good health and a long life, there is probably no single one way and as told in the post Miracle Food for Thought:
“The facts about the latest dietary discoveries are rarely as simple as the headlines imply. Accurately testing how any one element of our diet may affect our health is fiendishly difficult. And this means scientists’ conclusions, and media reports of them, should routinely be taken with a pinch of salt.”
It’s about the same with data quality, isn’t it?
Accurately testing how any one element of our data may affect our business is fiendishly difficult. So predictions of return of investment (ROI) from data quality improvement are unfortunately routinely taken with a big spoon of salt.
Also as discussed in the post Turning a Blind Eye to Data Quality there are plenty of examples of business success despite of poor data quality.
So, no, there is no single secret behind good data quality. But there is a wealth of good practices, tools and services to choose from out there.