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Data Lakes auf den Grund gegangen

Herausforderungen und Forschungslücken in der Industriepraxis

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Zusammenfassung

Unternehmen stehen zunehmend vor der Herausforderung, große, heterogene Daten zu verwalten und den darin enthaltenen Wert zu extrahieren. In den letzten Jahren kam darum der Data Lake als neuartiges Konzept auf, um diese komplexen Daten zu verwalten und zu nutzen. Wollen Unternehmen allerdings einen solchen Data Lake praktisch umsetzen, so stoßen sie auf vielfältige Herausforderungen, wie beispielsweise Widersprüche in der Definition oder unscharfe und fehlende Konzepte. In diesem Beitrag werden konkrete Projekte eines global agierenden Industrieunternehmens genutzt, um bestehende Herausforderungen zu identifizieren und Anforderungen an Data Lakes herzuleiten. Diese Anforderungen werden mit der verfügbaren Literatur zum Thema Data Lake sowie mit existierenden Ansätzen aus der Forschung abgeglichen. Die Gegenüberstellung zeigt, dass fünf große Forschungslücken bestehen: 1. Unklare Datenmodellierungsmethoden, 2. Fehlende Data-Lake-Referenzarchitektur, 3. Unvollständiges Metadatenmanagementkonzept, 4. Unvollständiges Data-Lake-Governance-Konzept, 5. Fehlende ganzheitliche Realisierungsstrategie.

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Notes

  1. http://hadoop.apache.org/.

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Author information

Authors and Affiliations

  1. IPVS, Universität Stuttgart, Universitätsstraße 38, 70569, Stuttgart, Deutschland

    Corinna Giebler, Rebecca Eichler, Holger Schwarz & Bernhard Mitschang

  2. Robert Bosch GmbH, 70469, Stuttgart, Deutschland

    Christoph Gröger & Eva Hoos

Authors
  1. Corinna Giebler
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  2. Christoph Gröger
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  3. Eva Hoos
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  4. Rebecca Eichler
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  5. Holger Schwarz
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  6. Bernhard Mitschang
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Correspondence to Corinna Giebler.

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Giebler, C., Gröger, C., Hoos, E. et al. Data Lakes auf den Grund gegangen. Datenbank Spektrum 20, 57–69 (2020). https://doi.org/10.1007/s13222-020-00332-0

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  • DOI: https://doi.org/10.1007/s13222-020-00332-0

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