Data Science: Why In The Digital Age The Ability To Program And Encode Must Become Democratic And Widespread.

Today’s Success Is Not In Having More Information, But In The Ability To Learn From Large Amounts Of Data.

Right now everyone wants to learn Python. And it’s no coincidence.
Surveys and statistics according to the law of large numbers tend to demonstrate and manifest the evolution of collective intelligence, which if well balanced with individual rationality can be a strategic source from which to draw to make the best decisions in the presence of uncertainty.

Let’s start from a premise: programming is very easy, almost like thinking. What makes it difficult is the “fear of not understanding”.
To learn how to program one has to “get used to“, assimilating computational logic.
This is not a skill that is only required to engineers or graduates in technical fields, but today the ability to interact deeply with computer devices can be a key variable for professional success.
Not only directly through the production of integrated automated systems, but also through the computational logic that trains us to manage data and resources efficiently.

Programming is an increasingly necessary tool because two critical factors have coincided in recent years:
1) The data revolution
2) The computational power
The first refers to the increasing availability of online data, accessible and acquirable on which to work in order to extract knowledge useful for making decisions.

A possibility that has never existed before.

The second is the ability to manage that data thanks to increasingly powerful computers spread in a democratic way among the population.
Before now these 2 factors did not exist and therefore it was not possible to do all this.
Today, in a few moments, thanks to programming, it is possible to analyze and synthesize the knowledge coming from millions, if not billions, of data coming from all over the world in a few seconds.
This is a revolution that we must learn to manage as soon as possible, understanding its logic and mechanisms.
The discipline that deals with giving a formal structure to this set of skills is called Data Science, which provides for the union of statistical skills, programming and its domain of competence to create systems that produce knowledge.
In an economy where work is increasingly automated, it is in the ability to produce knowledge and innovation that the key variables for creating wealth are found.
But in order to ensure that the level of wealth is widespread and democratic, it is necessary that this knowledge and skills are spread and democratic among the population, avoiding the formation of a cognitive monopoly that makes the population dependent and slave to those who understand the operation of these mechanisms.
That the new skills are democratic and widespread is a key point for our society, a challenge in the coming years to be able to make accessible to all the tools to be able to become entrepreneurs and producers of tomorrow, because only by forming will not be the victim of an increasingly complex and interconnected digitalized world.