The research field of Data Analytics looks at the development and implementation of systems for the automatic analysis of heterogeneous electronic contents. Focus is placed on the analysis of structured corporate data (business intelligence), unstructured text and multimedia contents (web intelligence) as well as data sources with a high level of heterogeneity, large volumes and data throughput (big data). In particular, big data sources are becoming increasingly available thanks to new developments such as Industry 4.0, the Internet of Things (IoT) and social media as well as the trend towards quantified self.
Methods from the fields of natural language processing, machine learning, pattern recognition and information retrieval are often used for the evaluation of these sources. Examples include: (i) sentiment analysis for the assessment of text tonality; (ii) knowledge extraction in order to automatically recognise persons and organisations using named entity linking and to assign the corresponding data sets in linked open data repositories and relational databases; (iii) social network analyses in order to identify relationships between persons and organisations; or also (iv) data enrichment methods for the automatic annotation of texts, images and multimedia contents.
Due to the constantly increasing availability of relevant data sources, ever more efficient analysis methods and their relevance for industrial applications, the ability to analyse internal and external data and to use this data to make decisions, optimise business processes and develop new products will in the near future play a key role with respect to the competitiveness of companies and public institutions. The research field of data analytics views itself as a catalyst of this digital transformation and works on technologies that lead to increased efficiency as well as product and process innovations.
Through the use of data analytics in companies, management staff have the tools required to find those pieces of data within the growing wealth of information available that can help to generate new knowledge and thus gain an innovative edge. On the way to becoming a learning organisation, these are decisive success factors in allowing a company to make implied knowledge explicit, distribute this knowledge and make optimal use of it. This also includes the successful use of social networks as important tools for internal and external communication strategies. With the help of our data analytics research, we are able to identify knowledge within companies and visualise the knowledge relationships. These companies thus gain an effective and efficient overview of their entire business.
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