THE MATURATION OF DATA SCIENCE

THE MATURATION OF DATA SCIENCE

By W H Inmon

Data science and data scientists are immature. This is not a pejorative statement but merely a statement of historical fact. Data science has been around for a very short amount of time, maybe five years, depending on how you count. So data science is still in its infancy. Other professions have been around for millenia. Data science has not even been around for a decade. So it is simply a statement of historical fact that the profession of data science is immature.

The signs of the immaturity of data science are everywhere.

1)?????The data scientist has the attitude that they want to do it all. The data scientists goes to school, learns all this theory then comes into the real world and discovers that 95% of the time the data scientists is struggling and haggling with data. The data scientist gets to be a data scientist only a small fraction of the time. Most of the time the data scientist is a data garbageman. Consider the medical profession. Surgeons go to school and learn about all sorts of things about the human body. But when the surgeon goes out into the real world, the surgeon is always accompanied by an anesthesiologist. The surgeon knows that a team effort is required to conduct a successful surgery. The data scientist needs to be paired with a data architect in order to be freed from having to wrangle with data. This is one sign of the immaturity of data science. The data scientist does not want to be part of a team. The data scientist wants to be the lone ranger. The data scientist does not recognize that he/she needs Tonto in order to survive the dangers and challenges that await.

2)?????The data scientist starts with the proposition that that there is deep and mysterious data hiding in the corporation just waiting to be found. The role of the data scientist is to find that data and bring the business value out. This is putting the cart before the horse. While there indeed may be secret relationships of data that are of interest, it is far more productive for the data scientist to start with trying to solve a business problem rather than go looking for hidden patterns of data then derive the business value from those patterns. Another sign of immaturity.

3)?????The data scientists have a disdainful attitude to the other people in the organization. They don’t give anyone else credit for contributing to the success of understanding data. This snobbery alienates people and in many cases, leads to the downfall of the data science effort, not to the success of data science project. More immaturity.

4)?????The data scientist ignores sources of data that have been vetted and integrated. The data scientist thinks that only he/she has the background to vet and integrate data. This attitude just adds another obstacle to the achievement of success.

And there are lots other ways in which the data science profession is immature. This is just the tip of the iceberg.

That’s the bad news.

The good news is that there is a legitimate reason for doing data science. There are significant contributions that the data scientists can make (and ought to make). And like all mature professions, at the beginning every profession was once immature. But professions do mature over time.

(My dentist and I have a good laugh. In his office is a picture of dentistry as it was practiced in the old west. There is a poor soul sitting in a chair. There is a dentist trying to pluck out a tooth with pliers and a hammer. One can only image the agony of dentistry in the old west. Thank God for modern medicine and dentistry.)

So there is every reason to believe that in the future data science will start to make a real and positive contribution to business and the art of handling data. Maturity happens.

Bill Inmon lives in Denver with his wife and his two Scotty dogs – Jeb and Lena. Jeb and Lena don’t like it when it gets cold and starts to snow because that cuts into their daily walks. And they think they can’t live without their walks. (And their cookies.)