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Review of Descriptive Analytics Under Fuzziness

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Intelligent and Fuzzy Systems (INFUS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 505))

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Abstract

Business Analytics is one of the business management methods that deals with descriptive models which create meaningful insights to support and reinforce the business performance. It is one of the most widely used topics in business and Industry. The first state of each analytics is collecting valid data. Descriptive Analytics is the first stage of data processing that outlines historical data to acquire helpful information and organize the data for advanced analysis. In analyzing and classifying data from a statistical perspective, fuzzy sets and logic have become valuable tools to either model and handle imprecise data or establish flexible techniques to deal with precise data. Despite the popularity of Business Analytics in literature and the importance of Descriptive analytics as a first step, many aspects are still unclear. So due to the importance of Descriptive Analytics for organizations and the vagueness nature of data, we try to review Descriptive Analytics under fuzziness in this article.

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Author information

Authors and Affiliations

  1. Industrial Engineering Department, Urmia University of Technology, Urmia, Iran

    Elmira Farrokhizadeh

  2. Industrial Engineering Department, Istanbul Technical University, Istanbul, Turkey

    Başar Öztayşi

Authors
  1. Elmira Farrokhizadeh
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  2. Başar Öztayşi
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Corresponding author

Correspondence to Başar Öztayşi .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

  3. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  4. Department of Industrial Engineering, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  5. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Basar Oztaysi

  6. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

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Farrokhizadeh, E., Öztayşi, B. (2022). Review of Descriptive Analytics Under Fuzziness. In: Kahraman, C., Tolga, A.C., Cevik Onar, S., Cebi, S., Oztaysi, B., Sari, I.U. (eds) Intelligent and Fuzzy Systems. INFUS 2022. Lecture Notes in Networks and Systems, vol 505. Springer, Cham. https://doi.org/10.1007/978-3-031-09176-6_71

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