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  5. Databases & Big Data Databases & Big Data

Databases & Big Data Value creation from data  

Intelligent data management enables the generation of knowledge from data and its effective use for both economic and societal benefit.

Digital data is growing exponentially and as big data, it poses challenges in terms of volume, velocity, and variety. Traditional solutions are often no longer sufficient, as data can be extremely large, exist in diverse formats, or require real-time processing. Innovative methods allow large datasets to be processed efficiently and novel, heterogeneous data sources to be integrated. From this, knowledge can be extracted, clearly prepared, and made easily accessible – enabling users to act and make informed decisions based on data.

Die fünf V’s von Big Data nach Demchenko et al. 2013.

Researchers at the Lucerne School of Computer Science and Information Technology work closely with partners from both industry and academia. They develop and evaluate new methods, models, algorithms, and systems to effectively address data-driven challenges. They build software prototypes – from early demos to MVPs – and test them under real-world conditions in order to assess their impact. In doing so, they support industry partners in developing innovative products and processes. The insights gained contribute to advancing the scientific state of the art.

Our researchers advise and support partners using both established and experimental approaches. They design, test, and implement every step – from raw data to actionable insights and data-informed decisions. To this end, they develop and research practical systems and scientifically sound methods in the following areas:

  • Data Management: Strategies for data governance and data value creation
  • Business Intelligence: Interactive dashboards and data warehousing with SQL
  • Data Science: Modeling with R and Python for data mining and data analytics
  • Cloud Databases: Modern data platforms for large-scale data integration
  • Data Streams: High-performance parallel and probabilistic algorithms
  • Information Extraction: Natural language processing for data lakes
  • Graph Databases: Scalable network analysis with Cypher and GQL
  • Database Security: System architectures and methods to protect valuable data

Would you like to work with us on data projects that deliver both economic and societal impact? We look forward to hearing from you.

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Selected publications

  • Stechschulte, G., Wintner, M., Hemmje, M., Schwarz, J., Lischer, S., & Kaufmann, M. (2024). In-Database Feature Extraction to Improve Early Detection of Problematic Online Gambling Behavior. IEEE Transactions on Computational Social Systems, 11(5), 6868–6881. IEEE Transactions on Computational Social Systems. https://doi.org/10.1109/TCSS.2024.3406501
  • Kaufmann, M. (2023). Emergent Knowledge Engineering in Big Data Management [Habilitationsschrift, FernUniversität in Hagen]. https://ub-deposit.fernuni-hagen.de/receive/mir_mods_00001905
  • Kaufmann, M., & Meier, A. (2023). SQL and NoSQL Databases: Modeling, Languages, Security and Architectures for Big Data Management. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-27908-9
  • Giesser, P., Stechschulte, G., Costa Vaz, A. da, & Kaufmann, M. (2021). Implementing Efficient and Scalable In-Database Linear Regression in SQL. 2021 IEEE International Conference on Big Data (Big Data), 5125–5132. https://doi.org/10.1109/BigData52589.2021.9671865
  • Kaufmann, M. (2019). Big Data Management Canvas: A Reference Model for Value Creation from Data. Big Data and Cognitive Computing, 3(1), 19. https://doi.org/10.3390/bdcc3010019

Your contact person

Prof. Dr. habil. Michael Kaufmann

Lecturer and Project Manager

+41 41 757 68 48

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Computer Science and Information Technology Blog

  • «Wir werden das Machine Learning direkt innerhalb von Datenbanken optimieren»
  • Eiger, Mönch und… Willisau?

Degree Programmes

  • Bachelor in Informatik oder Wirtschaftsinformatik, Major Data Engineering & Data Science (Only in German)
  • Master in Applied Information and Data Science
  • Master of Science in Engineering, Profile Data Science

Continuing and Executive Education

  • Data Intelligence & Big Data

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Lucerne School of Computer Science and Information Technology


Campus Zug-Rotkreuz

Suurstoffi 1
6343 Rotkreuz

+41 41 757 68 11

informatik@hslu.ch

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