TU Berlin

Data Analytics LabMission

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The primary mission of the Data Analytics Laboratory includes:

  •  meeting the needs of data scientists, by devising solutions that can simultaneously cope with the volume, velocity, variety, and veracity aspects of data analytics,
  •  developing novel statistical & mathematical algorithms, prediction techniques, modeling methods, compression schemes, as well as new approaches for data collection, integration, and data/information sharing technologies,
  • opening up new ways of extracting useful, reliable, and verifiable information from monstrous data sets, swiftly using advances in information processing, integration, signal processing, machine learning, data mining, compression, and visualization,
  • establishing a pipeline to prepare the data science leaders of tomorrow and narrow the gap in the expected shortfalls for qualified data scientists,
  • focusing on holistic data science research and education addressing the challenges of large data sets, high ingestion rates, short analysis time windows, different content and media types, and contradicting, incorrect, and missing information,
  • educating data scientists who will be well prepared to develop innovative data analysis tools, develop scalable data processing systems, and showcase their solutions to challenging real-world use cases of relevance to science, industry, and society,
  • leveraging the EIT (European Institute of Technology) located at TU Berlin and its established partnerships with large enterprises and SMEs, closing the loop between research, education, and innovation, including the larger big data ecosystem in Berlin with research institutes (e.g., Fraunhofer HHI, Fraunhofer FOKUS, DFKI), Charité, SMEs and the Berlin startup scene.


The Technische Universität Berlin aims to be a premier academic institution with technical expertise in the emerging data science field.

Our vision is to conduct groundbreaking research and development and prepare tomorrow’s data science researchers to address grand challenge problems.





Your application for an individual "consultation hour" with one of our "Data Science and Engineering" advisors, please send/give to:   

Claudia Gantzer, +49 314 23555 / room EN-728 / email: 


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