The world of science and industry has undergone a profound transformation. Data is readily available at large-scales – derived from sensors, the web, varying transactions, and complex simulations. However, today’s information systems are ill adept at optimally processing and analyzing it for several reasons, including data:
- volume, alluding to the sheer size of data sets, in the terabyte or petabyte range and beyond,
- variety, referring to the diversity of digital formats, such as audio, sensor data, text, or video,
- velocity, designating that data must be processed within strict time bounds in order to arrive at actionable information, and
- veracity, concerning the accuracy and credibility of analyses, given that data originates from distinct sources with variable quality and trustworthiness levels.
Indeed, even data visualization presents numerous difficulties, particularly for highly dynamic, voluminous data sets. Thus, in order to push the envelope beyond the state-of-the-art, Technische Universität Berlin researchers are steadfastly developing novel solutions to capitalize on the available data and advance data-driven decision-making.
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Data Science and Engineering Track ContactDr. Ralf-Detlef Kutsche
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