Practical Problems in Customer Data — A Use-Case-Driven Classification

Deinhard JL, Lenz R (2025)

Publication Type: Conference contribution

Publication year: 2025

Conference Proceedings Title: P361 - BTW2025 - Datenbanksysteme für Business, Technologie und Web

Event location: Bamberg DE

DOI: 10.18420/BTW2025-24

Abstract

This article presents a comprehensive analysis of data quality issues encountered in customer data at large enterprises. This analysis is based on data collected at a large medical technology manufacturer, and the problems observed there are clustered into distinct classes. Through this classification, nine key prevention requirements can be identified which are essential for improving data fitness. These include changes to data governance and to data architecture, among others. An evaluation of existing tools against these requirements furthermore highlights notable solutions. Despite the availability of numerous tools, gaps remain, especially regarding integration of all functionalities. Our findings suggest that while industry-standard solutions are accessible, integrating them into a cohesive framework posed significant challenges in our use case, necessitating continual adjustments to data architecture and processes to enable and maintain high quality of data.

Authors with CRIS profile

Jan-Lucas Deinhard Professur für evolutionäres Datenmanagement Richard Lenz Professur für evolutionäres Datenmanagement

How to cite

APA:

Deinhard, J.-L., & Lenz, R. (2025). Practical Problems in Customer Data — A Use-Case-Driven Classification. In P361 - BTW2025 - Datenbanksysteme für Business, Technologie und Web. Bamberg, DE.

MLA:

Deinhard, Jan-Lucas, and Richard Lenz. "Practical Problems in Customer Data — A Use-Case-Driven Classification." Proceedings of the BTW2025 - Datenbanksysteme für Business, Technologie und Web, Bamberg 2025.

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