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Information Processing and Data Analytics for Decision Making: A Journey From Traditional to Modern Approaches

Author

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  • Pooja Nanda

    (New Delhi Institute of Management, India)

  • Vikas Kumar

    (Central University of Haryana, India)

Abstract

Decision making is required by all organizations; however, the decision making styles may differ. ost commonly used decision styles include: (a) Autocratic (b) Democratic (c) Consensus and (d) Participatory. With the Globalization and expansion of businesses, professionals have become highly dependent upon the technology to support the decision making process and decision support systems have come-up as a fastest growing discipline. Present work discusses the evolution of computerized decision support, considering the: (a) Model Driven (b) Data Driven (c) Communication Driven (d) Document Driven and (e) Knowledge Driven decision support systems. All three different business levels: Operational, Tactical and Strategic have been considered in the present work to review the development of decision support systems. The traditional data analysis based approaches have been compared with the latest data analytics approaches including the social media analytics and web analytics. Examples from the different industry sectors have been incorporated for better illustrations of decision support.

Suggested Citation

  • Pooja Nanda & Vikas Kumar, 2022. "Information Processing and Data Analytics for Decision Making: A Journey From Traditional to Modern Approaches," Information Resources Management Journal (IRMJ), IGI Global, vol. 35(2), pages 1-14, April.
    • Handle: RePEc:igg:rmj000:v:35:y:2022:i:2:p:1-14
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IRMJ.291693
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    Cited by:

    1. Sumets, Alexander & Heorhiadi, Nelli & Tyrkalo, Yuriy & Vilhutska, Roksolana & Pylypenko, Iov, 2023. "Modeling of the information system for agribusiness management entities," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(2), June.

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