Big Data have arrived on tennis and volleyball courts. Extracting value from data and statistics has become so important that the number one tennis player Novak Djokovic decided to bring in a Data Scientist to his team, Craig O’Shannessy, who has been developing mathematical models based on information from the ATP and WTA circuits for years. A winning choice given that O’Shannessy himself, in the column he writes for the ATP website, explains what were the tactics that the Serbian tennis player he “assisted” followed to beat Rafael Nadal in the recent final of the Australian Open.
There is talk of a “virtual coach” driven by data and algorithms in volleyball too, where the mathematical models by a team of experts contributed to bring home the silver medal at the World Championships by the Women’s National Team coached by Davide Mazzanti, who was so convinced of the virtue of relying on Big Data analysis that he kept a Data Scientist on the bench during the Italian stages of the Volleyball Nations League and during the Olympic qualifiers. In the case of volleyball, algorithms are able to analyze the on-court footage of the players, extracting data useful for describing the movement of the athletes, comparing them with the ball’s trajectory and the result achieved, in order to suggest how they could improve to “score a point”.
What is the Big Data market?
According to IDC, the Big Data and analysis software market, which in 2017 reached $ 54.1 billion worldwide, is expected to grow at a 5-year CAGR (compound annual growth rate) of 11.2%, reaching $ 92.1 billion in 2022.
There are three trends which will most impact on this forecast: the growing importance of data within companies and the awareness that their positioning can be improved through these; the many companies which now resort to the public Cloud and, thirdly, the use of Artificial Intelligence and of Machine Learning (ML) in corporate processes.
The Big Data and Analytics (BDA) software market, which includes analytical and performance management applications (APM), business intelligence and analysis tools (BIA) and the analytical data management and integration platforms (ADMI), is also growing.
How is the demand for software changing?
According to IDC, most providers of data management and analysis applications already include features such as predictive analytics, machine learning and the possibility to process automated forecasts. We will have to increasingly imagine products capable of incorporating advanced analysis capabilities, that also guarantee transparency for users.
The demand for software for AI platforms and for information analysis tools based largely on deep learning will continue to grow consistently over the next few years. In the period up to 2022, IDC predicts that suppliers will focus on exploiting AI which can help to improve data reading and understanding.
New software purchases will certainly be influenced by the availability of applications which include the integration of artificial intelligence, considered by many particularly advantageous for managing corporate processes.
How has the demand for professional skills changed?
As business needs and technologies evolve, the necessary professional skills are changing: according to the Osservatorio Big Data Analytics & Business Intelligence of the Management School of the Politecnico di Milano, in fact, the need for Data Science skills is growing. So much so that 46% of large companies has already included Data Scientist figures in their workforce, 42% Data Engineers, 56% Data Analysts. A change which is only just beginning and that does not envisage, in most cases, a variation in the organizational model, which often remains the traditional one.
