Back in 2006, British mathematician Clive Humby penned a phrase that would later become the slogan for defining the fourth industrial revolution: “Data is the new oil“. Data constitute an asset capable of reshaping the market and society, creating new business opportunities and new professions, much like oil did in the 19th and 20th centuries.
Technological advances over the last 15 years have also contributed to the exponential and continuous growth of data, increasing the type of information that can be processed. We are surrounded by Big Data, Open Data, cloud and databases, most of them produced by IoT devices and sensors, such as voice assistants, GPS and smartphones. Data Science came into existence in this ever-changing and virtually unstoppable context as a complex discipline encompassing the entire information production chain, from collection to processing and critical analysis of results, data science is strategic for our future. Its power to forge links between academic research and the business world and to cut across all productive sectors, given the ubiquity of data, has placed the data scientist among the most sought-after professions, especially among STEM graduates.
But just how much do we know about this new black gold and the skills needed to become a data scientist? During the talk “Data Science, the future is in the data“, PHYD posed the question to Microsoft experts Luca Malinverno and Franco Pigoli, respectively data scientist and education manager at Porini, a company specialising in ERP and one of Microsoft’s main international partners.
Malinverno recommends to start by giving a definition, however general it may be, to understand what we are talking about: “Every science is intrinsically linked to data, drawing from data to observe reality. Yet unlike other scientific disciplines, Data Science does not use data to study a human or natural phenomenon; its object of study is the data itself“. And studying data means knowing and understanding the world around us, understanding the causal links between events, predicting behaviour, anticipating needs, reducing errors. We can harness data to gain real insight into customer profiles on an e-commerce platform, for example, or to define market trends. Data science can therefore embrace a wide range of applications, including IoT, machine learning and AI, and its constant developments may expand its scope to quantum computing. The required skills are thus also growing and changing.
Unlike other scientific disciplines, Data Science does not use data to study a human or natural phenomenon; its object of study is the data itself.
Luca Malinverno, data scientist
Malinverno believes that to become a good data scientist, “you have to like puzzles or riddles, because you have to answer questions that are sometimes really complicated. You also need to possess strong analytical and mathematical skills, alongside a solid understanding of computers as a calculation tool. Data Science is still a frontier discipline that we are building today”.
The academic and business worlds play a key role in this unravelled path: Only collaboration and proximity between these two realities can foster the formation of a class of trained and experienced scientists. This is because, while theoretical foundations are paramount, STEM subjects or econometrics courses provide a solid phenomenological starting point, they are not enough on their own; reality is increasingly complex and unpredictable. Professional academies, highly specialised vocational training academies that equip future data scientists with the right mindset to properly enter the world of work, can bridge the gap between university and business.
Data Science is still a frontier discipline that we are building today.
Luca Malinverno, data scientist
No one can predict which path this discipline will take in the near future, which skills or attitudes it will require, but we are undoubtedly in the midst of change and immersed in an ocean of information and questions waiting to be processed and answered. What is certain, however, as Franco Pingoli comments, is that “people who play with data never get bored“.
To learn more about the topic and view the webinar, simply sign up on the PHYD website.