A – good-visualization also allows people who speak different (subject) languages to understand each other. For this, not everyone has to be a statistics expert, a basic knowledge of data handling and the right tools for presentation are enough. […]
Can you ever have enough data? For quantitative researchers, there often does not seem to be enough. The amount of data collected in and for science has grown exponentially in recent years. This means that insights can increasingly be gained based on thousands or millions of data points.
But apart from the analysis skills that are needed for this, this trend is accompanied by a new need: New and better visualization skills are needed to convey the results of such analyses, to make them vivid and to make the pin in the haystack visible. This ability is also increasingly in demand in the economy. It is therefore becoming increasingly important for universities to equip young people with precisely this knowledge. The motto: Sowing data competence, harvesting visualizations.
Data literacy is as important as reading, writing and arithmetic. It is the basic skill for generating, understanding and finally also visualizing data and thus a key topic for living and working in a networked world with its abundance of data. It is also a prerequisite for the presentation and interpretation of data. More and more universities and application-oriented universities are therefore working to impart such data competence to their students and also to enable their own researchers to do so.
The benefits of good data visualization can hardly be overestimated. It is a communication tool that will continue to gain in importance, especially in the networked, interdisciplinary world of research and teaching. In empirical and quantitative research, however, research results are usually prepared in the form of tables and columns of numbers. The language of statistics forms the common basis of communication among experts across subject boundaries. But in order to meet societal challenges comprehensively, visualizations can overcome barriers to understanding more easily even among laypersons and thus make research results more accessible to a larger audience.
As far as theory – in practice, the correct handling of data often finds no place on the curriculum either at schools or at universities. And data visualizations are still neglected in too many subjects. For example, many university graduates, whether they are pursuing a career in science or industry, have to acquire the required skills for handling data and presenting it on the job.
However, there are also positive examples. For example, at the Münster University of Applied Sciences and the Münster School of Business, students can learn the responsible handling of data, its preparation, analysis and visualization, among other things in controlling events. This includes the planned and goal-oriented handling of data and basic knowledge as well as the use of analytics software for data visualization. In this way, students learn what they need for their later task – providing management with decision – relevant information. Skills in data visualization are a necessary foundation for optimally fulfilling this task in a data-driven, digital world.
In the courses, students not only work on classic business administration topics. In semester-accompanying data projects, you can follow personal interests and visualizations on topics such as climate change, sports, corona or music are created. Finn Dörnenburg and Jan Werner, for example, analysed the music of the band Linkin Park in a Data viz.
Interactive data visualization by students Finn Dörnenburg and Jan Werner on Tableau Public (c) Tableau
In this way, students playfully learn the effective and efficient handling of data. The result: as valuable employees, you can help shape the digital transformation in companies.
A good data visualization makes facts comprehensible, understandable and tangible. At best, it enables the viewers themselves to ask critical questions or make judgments.
In the 19th century, scientists such as John Snow, the founder of modern epidemiology, had to carry out elaborate manual analyses and visualizations. Today, virtually every scientist, but also students and laymen, can map time courses or maps with a little training – even interactively. Thanks to software, more people than ever before have the opportunity to develop advanced visualizations.
The special thing about the new visualizations, as they can be explored on Tableau Public, for example: they are interactive. They allow anyone to interact with the data by changing filters and parameters. In this way, the larger context in which a result is located can be actively controlled by the viewer and experienced visually. In this presentation, the data no longer only present the author’s perspective on a topic. Rather, the user himself can ask questions to the visualization and receives answers, always taking into account the larger contexts.
While institutional training – from school to university-in the field of data visualization can still increase, the community of visualization fans is growing rapidly and is already internationally networked. Data-savvy people are looking for exchange, find suggestions and present and share their own visualizations. Those who have the appropriate education and a passion for the subject live the much-touted data competence and constantly develop it. This shows that not only is there a need for these skills, but also that there are many people who enjoy precisely these tasks and challenges and who are constantly pushing the boundaries of what data and its visualization mean. Access to this community is open to all interested parties.
* Klaus Schulte is Professor of Controlling at the University of Applied Sciences Münster. The Tableau Zen Master and IronViz Champion offers hands-on training for data preparation and data visualization in their Bachelor’s and Master’s courses.