Last week I had the honor of participating in a very interesting round table, organized by SAS, about the future of the insurance sector. An obligatory topic was technology and, of course, the lack of qualified personnel in Spain emerged to meet the great demand for data analytics.
It is a real problem. There is a lack of programmers, there is a lack of analysts and, especially, the so-called data scientists. But I go one point further. The problem is not only that there is a lack of experts in extracting data. The problem is that, of those who know how to do it, very few know how to interpret them. So the lack is even greater.
My opinion is that we should not talk about data scientists as much as data humanists. Behind a data there is always a person. A piece of data is a record of something, of a trace that we have left on social networks, of a search in the browser, of an email, of a photo on Instagram, of a visit to a web page, of an online purchase, of a credit card payment… In short, almost everything we do, because our day-to-day life is irremediably recorded in global big data.
So data is nothing without people. And the data reflects that, our lives. Behind the cold data there are emotions, motivations, doubts, feelings, desires, illusions and disappointments. Behind the data there are real stories, and data, above all, means things. Humanistic university degrees teach our young people to interpret the world, but they hardly learn anything about data analytics or study programming. Data mining or computer science degrees, and even STEM profiles, know how to extract information and perform calculations, but they lack a systemic and comprehensive vision of human beings, their anthropology and psychology. They are two disciplines that, separated, are incomplete and, on the contrary, together they make up the current representation of the world and man.
The university system runs as fast as it can. And he runs a lot! There are new degrees, and the different itineraries and study plans have become much more flexible, but the problem is that technology moves much faster. It’s impossible to keep up with his pace. So companies have no choice but to develop their own training schools, create specific programs that cover the gaps that technology produces. And within these gaps, from my point of view, the most pressing is that of forging data humanists, data humanists.
