Analytics in Industry 4.0: Investigating the Challenges of Unstructured Data

被引:1
|
作者
Moehring, Michael [1 ]
Keller, Barbara [3 ]
Schmidt, Rainer [2 ]
Schoenitz, Fabian [3 ]
Mohr, Frederik [3 ]
Scheuerle, Max [3 ]
机构
[1] Reutlingen Univ, Fac Comp Sci HHZ, Alteburgstr 150, D-72762 Reutlingen, Germany
[2] Munich Univ Appl Sci, Sch Comp Sci & Math, Lothstr 35, D-80335 Munich, Germany
[3] Cooperat State Univ Baden Wuerttemberg, DHBW Stuttgart, Business Informat Syst, Paulinenstr 50, D-70178 Stuttgart, Germany
关键词
Unstructured data; Industry; 4.0; Data analytics; Information; systems; Data science; BIG DATA; INFORMATION-SYSTEMS; INTERNET;
D O I
10.1007/978-3-031-16947-2_8
中图分类号
F [经济];
学科分类号
02 ;
摘要
Data analysis is becoming increasingly important to pursue organizational goals, especially in the context of Industry 4.0, where a wide variety of data is available. Here numerous challenges arise, especially when using unstructured data. However, this subject has not been focused by research so far. This research paper addresses this gap, which is interesting for science and practice as well. In a study three major challenges of using unstructured data has been identified: analytical know-how, data issues, variety. Additionally, measures how to improve the analysis of unstructured data in the industry 4.0 context are described. Therefore, the paper provides empirical insights about challenges and potential measures when analyzing unstructured data. The findings are presented in a framework, too. Hence, next steps of the research project and future research points become apparent.
引用
收藏
页码:113 / 125
页数:13
相关论文
共 50 条
  • [1] Collaborative Data Analytics for Industry 4.0: Challenges, Opportunities and Models
    Lazarova-Molnar, Sanja
    Mohamed, Nader
    Al-Jaroodi, Jameela
    [J]. 2018 SIXTH INTERNATIONAL CONFERENCE ON ENTERPRISE SYSTEMS (ES 2018), 2018, : 100 - 107
  • [2] Data Analytics Challenges in Industry 4.0: A Case-Based Approach
    Brichni, Manel
    Guedria, Wided
    [J]. ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS (OTM 2018), PT II, 2018, 11230 : 209 - 221
  • [3] Data Analytics in Industry 4.0: A Survey
    Duan, Lian
    Xu, Li Da
    [J]. INFORMATION SYSTEMS FRONTIERS, 2021,
  • [4] Big data analytics in Industry 4.0 ecosystems
    Aujla, Gagangeet Singh
    Prodan, Radu
    Rawat, Danda B.
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2022, 52 (03): : 639 - 641
  • [5] A Big Data Analytics Architecture for Industry 4.0
    Santos, Maribel Yasmina
    Oliveira e Sa, Jorge
    Costa, Carlos
    Galvao, Joao
    Andrade, Carina
    Martinho, Bruno
    Lima, Francisca Vale
    Costa, Eduarda
    [J]. RECENT ADVANCES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2, 2017, 570 : 175 - 184
  • [6] INTELLIGENT PRODUCTION DATA ANALYTICS FOR METAL INDUSTRY 4.0
    Perzyk, Marcin
    Kozlowski, Jacek
    [J]. 27TH INTERNATIONAL CONFERENCE ON METALLURGY AND MATERIALS (METAL 2018), 2018, : 1835 - 1840
  • [7] Privacy Preserving Unstructured Big Data Analytics: Issues and Challenges
    Mehta, Brijesh B.
    Rao, Udai Pratap
    [J]. 1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015, 2016, 78 : 120 - 124
  • [8] Industry 4.0, Big Data Analytics and Transformation in Tax Systems
    Ilgun, M. Fatih
    [J]. MALIYE DERGISI, 2020, (179): : 240 - 266
  • [9] MOMIS Dashboard: A Powerful Data Analytics Tool for Industry 4.0
    Magnotta, Luca
    Gagliardelli, Luca
    Simonini, Giovanni
    Orsini, Mirko
    Bergamaschi, Sonia
    [J]. TRANSDISCIPLINARY ENGINEERING METHODS FOR SOCIAL INNOVATION OF INDUSTRY 4.0, 2018, 7 : 1074 - 1081
  • [10] Building an Industry 4.0 Analytics PlatformPractical Challenges, Approaches and Future Research Directions
    Christoph Gröger
    [J]. Datenbank-Spektrum, 2018, 18 (1) : 5 - 14