In the age of the Internet of Things and big data, data is becoming an increasingly important resource for businesses. It is even frequently referred to as "the new gold". But is it really the data itself that is so valuable? Not exactly. Rather, it is the insights that can be derived from it. That’s why businesses are increasingly looking for experts who are able to analyze large, complex volumes of data and draw the right conclusions to devise more efficient business strategies. A new occupation named "data scientist" is taking hold in the IT world, combining various job roles and responsibilities from the big data market.
But what exactly does a data scientist do? In general, it is an extension of the role of business or data analyst. While the conventional data analyst just analyzes data from one source, data scientists delve into and examine all data sources within a business—a process known as data mining. They are able to recognize patterns and uncover trends, even in masses of unstructured data. These insights are extremely valuable as they show businesses how they can better align their strategy to the customers’ needs.
So, data scientists are important—but where do they come from? At least until recently, there were no university programs in data science, so many still learn the ropes in business studies, computer science, or mathematics courses. In most cases, studying just one of these courses is not enough; data scientists require expertise in a variety of fields. In addition to technical knowledge, they need to be able to think both analytically and creatively. The path to becoming a big data specialist is very distinct.
Many data analysts, who are now referred to as data scientists, have acquired the necessary knowledge over the years through experience and on their own initiative. But a market for training courses has now developed, enabling IT professionals to specifically expand their skill sets. A growing number of companies, universities, and research institutes are offering workshops, seminars, and tutorials in big data. The Fraunhofer Institute for Intelligent Analysis and Information Systems is just one example. Participants usually receive a certificate at the end of such training programs.
Things are also starting to happen in university education. The economy’s demands for study programs with a specific focus on big data seem to have fallen on fertile ground. In 2013, US President Barack Obama declared data science as the top priority in the education sector. He pledged a total of 37.8 million dollars to universities in a bid to boost education in this field. His efforts were a success: Data science is one of the most popular subjects among applicants to universities such as Stanford and UC Berkeley.
This trend is catching on in Europe too, with numerous universities offering specialized study programs. The majority of these are comprehensive, in-depth master’s courses. Examples include Business Intelligence and Analytics at the Chemnitz University of Technology, Data Science at the Technical University of Dortmund, and Business Informatics with a focus on big data and business analytics at Aalen University. It is a growing trend: Even smaller institutes have jumped on the bandwagon and are expanding their range of courses.
However, courses in data science are still relatively new, giving graduates even better chances on the job market. To meet the global demand for big data specialists, the selection of courses offered needs to be expanded over the next few years.
At CeBIT, IT and business experts discuss how intelligent big data analyses transform entire business models. In forums, panel discussions, and workshops, visitors can discover the latest trends in big data, business intelligence, and predictive analytics . And the Job and Career area is the perfect place for data scientists who want to meet attractive employers or recruiters looking for highly sought-after IT specialists.