TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publications
  4. A systematic classification of database solutions for data mining to support tasks in supply chains
 
Options

A systematic classification of database solutions for data mining to support tasks in supply chains

Citation Link: https://doi.org/10.15480/882.3121
Publikationstyp
Conference Paper
Date Issued
2020-09-23
Sprache
English
Author(s)
Hunker, Joachim  
Scheidler, Anne Antonia  
Rabe, Markus  
Herausgeber*innen
Kersten, Wolfgang  orcid-logo
Blecker, Thorsten  orcid-logo
Ringle, Christian M.  orcid-logo
TORE-DOI
10.15480/882.3121
TORE-URI
http://hdl.handle.net/11420/8011
First published in
Proceedings of the Hamburg International Conference of Logistics (HICL)  
Number in series
29
Start Page
395
End Page
425
Citation
Hamburg International Conference of Logistics (HICL) 29: 395-425 (2020)
Contribution to Conference
Hamburg International Conference of Logistics (HICL) 2020  
Publisher Link
https://www.epubli.de/shop/buch/Data-Science-and-Innovation-in-Supply-Chain-Management-Wolfgang-Kersten-9783753123462/106047
Purpose: Our research shows that considering well suited NoSQL databases is ben-eficial for logistics tasks. For answering tasks we rely on the widespread methods of Data Mining. We stress that using relational databases as basis for Data Mining tools cannot cope with the growing amount of data and that using NoSQL databases can be an important step to address these issues. Methodology: This paper discusses Data Mining in the context of Supply Chain Man-agement tasks in logistics and its requirements on databases. The paper demon-strates that using NoSQL databases as basis for Data Mining process models in logis-tics is a very promising approach. The research is based on a case study, whose core element is the analysis of different well established studies. Findings: The paper presents results which show that Data Mining tools widely sup-port NoSQL databases through available interfaces. Findings are presented in a com-parison table which considers dimensions such as Data Mining tools and supported NoSQL databases. To show practical feasibility, a Data Mining tool is used on data of a Supply Chain stored in a NoSQL database. Originality: The novelty of this paper emerges from addressing issues that have so far been insufficiently analyzed in the scientific discussion. The modular structure of the addressed research method ensures scientific traceability. Breaking down tasks and their requirements on databases in the field of Data Mining is a first step towards meeting trends like Big Data and their challenges.
Subjects
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
DDC Class
330: Wirtschaft
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by-sa/4.0/
Loading...
Thumbnail Image
Name

Hunker et al. (2020) - A systematic classification of database solutions for data mining to support tasks in supply chains.pdf

Size

1.18 MB

Format

Adobe PDF

TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback