Sanitizing data for analysis: Designing systems for data understanding

Joshua Holstein (), Max Schemmer (), Johannes Jakubik (), Michael Vössing () and Gerhard Satzger ()
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Joshua Holstein: Karlsruhe Institute of Technology Kaiserstraße
Max Schemmer: Karlsruhe Institute of Technology Kaiserstraße
Johannes Jakubik: Karlsruhe Institute of Technology Kaiserstraße
Michael Vössing: Karlsruhe Institute of Technology Kaiserstraße
Gerhard Satzger: Karlsruhe Institute of Technology Kaiserstraße

Electronic Markets, 2023, vol. 33, issue 1, No 51, 18 pages

Abstract: Abstract As organizations accumulate vast amounts of data for analysis, a significant challenge remains in fully understanding these datasets to extract accurate information and generate real-world impact. Particularly, the high dimensionality of datasets and the lack of sufficient documentation, specifically the provision of metadata, often limit the potential to exploit the full value of data via analytical methods. To address these issues, this study proposes a hybrid approach to metadata generation, that leverages both the in-depth knowledge of domain experts and the scalability of automated processes. The approach centers on two key design principles—semanticization and contextualization—to facilitate the understanding of high-dimensional datasets. A real-world case study conducted at a leading pharmaceutical company validates the effectiveness of this approach, demonstrating improved collaboration and knowledge sharing among users. By addressing the challenges in metadata generation, this research contributes significantly toward empowering organizations to make more effective, data-driven decisions.

Keywords: Data understanding; Data governance; Metadata generation (search for similar items in EconPapers)
JEL-codes: L6 M15 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12525-023-00677-w

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