The Big Data Analytics Research Unit looks at the opportunities offered by analyses of Big Data . Read more about the focus of this research group.
Content element with id 11127
Digital sensors, the Internet of Things and social platforms are among the phenomena which nowadays generate a constant stream of new data. As the volume of this data increases at an ever-faster pace, more and more use is being made of Big Data analyses, which allow an unprecedented potential to be exploited in many areas of the economy. However, the generation and meaningful use of this wealth of information requires special technologies, approaches and systems. Our Big Data Analytics team tackles various aspects of Big Data with a focus on economic issues.
Special Focus
We specialise in the processing of structured and unstructured data generated by new methods and technologies. These include internet search queries, content from websites (job advertisements, invitations to tender, newspapers, prices) and information from social media.
Application to economic issues of Big Data methods such as machine learning with deep learning, data mining, natural language processing, time series analysis, etc.
Application of Big Data to business cycle research
Augmenting official statistics, for example for the labour market
Data economics including context-dependent economic analysis of law
Examples of current research
The Big Data Cooperation Cluster uses a wide range of analytical methods and approaches. In principle, Big Data methods can be applied to all pertinent economic issues. A typical example is the use of text analysis to analyse networks as in the case given here referring to the German players in Covid 19 research.
Obstacles to Data Sharing – An Outline of Recent Developments with Policy Recommendations
Marc Scheufen
The increasing networking of production processes and the ability of artificial intelligence to analyse ever larger amounts of data offer enormous potential for the German economy. To exploit this potential fully, however, data must be shared.
Generative AI in Germany:
Artificial intelligence in society and companies
Jan Büchel / Jan Felix Engler
Generative AI has recently caused quite a stir. The reason is that generative AI applications can independently generate content such as texts, images, programming codes or videos that are often difficult to distinguish from human-generated content.
Open Science as a Means for Development Aid:
Fostering Scientific Research and Innovation
*Alexander Cuntz / *Frank Mueller-Langer / *Alessio Muscarnera / *Prince C. Oguguo / Marc Scheufen
Access to prior scientific works and technical information is key to the emergence of new scientific knowledge and innovation (Moser and Biasi 2018, Nagler et al. 2019).
*Alexander Cuntz / *Frank Mueller-Langer / *Alessio Muscarnera / *Prince C. Oguguo / Marc Scheufen
IW
This website uses necessary cookies to ensure the operation of the website. An analysis of user behavior by third parties does not take place. You can find detailed information about the use of cookies in our privacy policy.
Warning: You are using an outdated browser!
Please switch to a modern browser (e.g. Google Chrome, Firefox or Microsoft Edge) in order to enjoy the best user experience.
