Viele bestehende Daten. Viele benötigte Kompetenzen.
Processing large volumes of diverse data at high speed – that’s the task faced by the Big Data experts. (© FH JOANNEUM / Manfred Terler)

A lot of data. A lot of skill sets.

Wolfgang Granigg,

What does Big Data stand for? What does it take to derive knowledge from large sets of data? And what do statistics and mathematics have to do with this? Wolfgang Granigg, interim head of the FH JOANNEUM degree programme in Data and Information Science* has the answers.

Big Data is a ubiquitous technical term not just in the traditional field of IT. Alongside cloud computing and the Internet of Things (IoT), Big Data is also responsible for a number of major thrusts in IT in the current decade. The pervasive use of the term means that it is increasingly associated with things and activities that essentially do not have much to do with the term “Big Data”.

By conventional definitions, the “big” in Big Data primarily refers to three attributes which further specify the term or rather the data at its centre: Firstly, it means “large volumes”, secondly “high speed” and thirdly “great variety”. “Big Data” could thus in summary be described as “large volumes of diverse data that are processed at high speed”. The verb “process” reflects the central challenges of this field: to effectively and efficiently collect, import, store, update, make available, analyse, aggregate, export, prepare or transmit such Big Data.

The integration of mathematical expertise and IT skills
While most activities require skills in information technology, the central analysis and aggregation of data calls for expertise in mathematics and statistics. Mathematics provides the basis for the sophisticated methods of analysis used in descriptive, inferential and exploratory statistics. The aggregation methods of multivariate statistics are also based on the concepts of higher mathematics, especially linear algebra and numerics.

In summary, this means that Big Data is in many respects an area of information technology, but when it comes to the central analysis and aggregation of data, it is primarily a mathematical-statistical discipline. This means that it calls for more than “just” programming and database management skills, namely also expertise in the fields of mathematics and statistics. If you further take into account the associated ethical and legal implications, Big Data must be considered as an interdisciplinary field. To work with Big Data therefore requires expertise in a whole range of areas.

The new Master's degree programme in Data and Information Science* at FH JOANNEUM starting in autumn 2018 is designed to provide comprehensive and practice-oriented training from the outset. Students learn the whole range of necessary skills, from IT and mathematics to the ethical and legal aspects of the discipline.

Please note: * subject to approval by the competent bodies.