What are the latest Big Data trends? The most "trivial" news is that the great Big Data revolution is making thousands of businesses more agile and efficient. And in very diverse sectors: retail, insurance and banking, marketing. Looking at the market numbers gives a great indication: a turnover of 103 billion dollars by 2027 worldwide, according to estimates by Statista. But it is not just a question of margins and productivity: the exploitation of Big Data allows customer loyalty, the forecast of consumer needs and the offer, therefore, of a faster service with a shorter waiting.
The banking sector is the one that most of all is exploiting the great potential of Big Data. According to the Big Data Analytics & Business Intelligence Observatory of the Politecnico di Milano, in 2018 banks represented the largest contribution to a sector, Big Data and Analytics, of over 1.3 billion euros in Italy, with a market share of 28%. How can all this be explained? First of all, because financial companies already have heterogeneous and massive data, two of the main characteristics of a solid Big Data base: the transaction history and current account movements, for example, to which less specific sources such as sentiment on social networks can be added. Such sentiment can also trends, reactions and perception. Italian Agos Ducato, active in the personal loan sector, has implemented Big Data and machine learning to automate the process of assigning credit to households both to offer a more streamlined service to its customers and to combat fraud. Another case of adoption is the Dutch ING (Internationale Nederlanden Groep) which, to further raise customer loyalty, offers a system of notifications in real time. The user thus receives a warning on their smartphone to immediately report any account situations in red or to proactively provide suggestions depending on the operations carried out more regularly by the account holder (such as a bank transfer sent to the same IBAN every week). In short, the Big Data trend in banks is that of rapid and pervasive growth.
For manufacturing, Big Data represented the way to stem one of the most long-standing problems in the sector: maintenance. Reducing operating costs, minimizing malfunctions and, above all, avoiding periods of inactivity due to inactive machinery are the three vectors that support the massive adoption of this data. According to the “Artificial Intelligence (AI) in Manufacturing Market” study by Global Market Insights, the Big Data trend in manufacturing is growing strongly. The use of Artificial Intelligence (especially through machine learning algorithms) will in fact reach 14.2 billion euros in 2025 with an annual growth rate of 40%. A situation resulting from the digital transformation accelerated by Industry 4.0, which involves, in addition to Artificial Intelligence, also robotics and IoT (Internet of Things). For this reason, today we talk about Intelligent Manufacturing: the adoption of intelligent models aimed at simplifying and at the same time the evolution of all lines of business. In Capgemini's "Smart Factories and the Modern Manufacturer" report it is estimated that smart factories will add 1.5 trillion dollars to the global economy and that in Italy 33% of manufacturers have already activated an initiative aimed at integrating smart factories in its own infrastructure.
When it comes to Big Data, telcos are the third sector in Italy by volume, behind banks and manufacturing, with a market share of 14%. On the other hand, it is a sector that is heavily "bombarded" with data and information on a daily basis, from users' web browsing on a fixed and mobile network to the millions of connected devices of an IoT ecosystem. Thus telcos can exploit Big Data to anticipate when a traffic peak will be recorded and thus organize their network so that there are no disservices for their customers. There are times of day or types of content (such as live Serie A matches), where the network is more congested. Ensuring that users can enjoy whatever content they want is essential to show the quality of the network itself. To achieve this, telcos around the world are exploiting Big Data to analyze when and how users use their network; what they consume, how much they browse and for how long. This set of data represents the basis for calibrating a network tailored to its customers.