Enterprise-Wide Metadata Management

Rebecca Eichler,Bernhard Mitschang,Christoph Gröger,Eva Hoos,Corinna Giebler,Holger Schwarz

doi:10.52825/bis.v1i.47

Rebecca Eichler, Bernhard Mitschang + Show 4 more

Open Access

https://doi.org/10.52825/bis.v1i.47

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Abstract

Metadata management is a crucial success factor for companies today, as for example, it enables exploiting data value fully or enables legal compliance. With the emergence of new concepts, such as the data lake, and new objectives, such as the enterprise-wide sharing of data, metadata management has evolved and now poses a renewed challenge for companies. In this context, we interviewed a globally active manufacturer to reveal how metadata management is implemented in practice today and what challenges companies are faced with and whether these constitute research gaps. As an outcome, we present the company’s metadata management goals and their corresponding solution approaches and challenges. An evaluation of the challenges through a literature and tool review yields three research gaps, which are concerned with the topics: (1) metadata management for data lakes, (2) categorizations and compositions of metadata management tools for comprehensive metadata management, and (3) the use of data marketplaces as metadata-driven exchange platforms within an enterprise. The gaps lay the groundwork for further research activities in the field of metadata management and the industry case represents a starting point for research to realign with real-world industry needs.

Highlights

In recent years, metadata management has regained focus in the scientific field and has once more become a topic of discussion in enterprises
We interviewed a globally active manufacturer to reveal how metadata management is implemented in practice today and what challenges companies are faced with and whether these constitute research gaps
An evaluation of the challenges through a literature and tool review yields three research gaps, which are concerned with the topics: (1) metadata management for data lakes, (2) categorizations and compositions of metadata management tools for comprehensive metadata management, and (3) the use of data marketplaces as metadata-driven exchange platforms within an enterprise

Summary

Introduction

Metadata management has regained focus in the scientific field and has once more become a topic of discussion in enterprises. Initiatives of both analytical systems such as data lakes and operational systems such as ERP systems and enables the access to and usage of metadata across the enterprise [3], for instance, in the form of a data-asset-inventory across various source systems Recent research, such as [3],[5],[6],[7],[8], mainly deals with metadata management explicit to data lakes, in which it is a central aspect [9]. In the context of becoming more data-driven, the manufacturer has implemented novel technologies and concepts such as data lakes, storage repositories for data at scale and analytical purposes [2], and aims to establish an environment in which data can be shared freely and efficiently within the enterprise With this goal the manufacturer aims to drive innovative data utilization and leverage more data value. The ability to perform more data analysis supports realizing industry 4.0 use cases like predictive maintenance or real-time manufacturing quality analysis [10]

DATA SHARING enables

Conclusion