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Proposal of Analytical Model for Business Problems Solving in Big Data Environment

Proposal of Analytical Model for Business Problems Solving in Big Data Environment

Goran Klepac, Kristi L. Berg
Copyright: © 2019 |Pages: 21
ISBN13: 9781522575016|ISBN10: 1522575014|EISBN13: 9781522575023
DOI: 10.4018/978-1-5225-7501-6.ch034
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MLA

Klepac, Goran, and Kristi L. Berg. "Proposal of Analytical Model for Business Problems Solving in Big Data Environment." Web Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 618-638. https://doi.org/10.4018/978-1-5225-7501-6.ch034

APA

Klepac, G. & Berg, K. L. (2019). Proposal of Analytical Model for Business Problems Solving in Big Data Environment. In I. Management Association (Ed.), Web Services: Concepts, Methodologies, Tools, and Applications (pp. 618-638). IGI Global. https://doi.org/10.4018/978-1-5225-7501-6.ch034

Chicago

Klepac, Goran, and Kristi L. Berg. "Proposal of Analytical Model for Business Problems Solving in Big Data Environment." In Web Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 618-638. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7501-6.ch034

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Abstract

This chapter proposes a new analytical approach that consolidates the traditional analytical approach for solving problems such as churn detection, fraud detection, building predictive models, segmentation modeling with data sources, and analytical techniques from the big data area. Presented are solutions offering a structured approach for the integration of different concepts into one, which helps analysts as well as managers to use potentials from different areas in a systematic way. By using this concept, companies have the opportunity to introduce big data potential in everyday data mining projects. As is visible from the chapter, neglecting big data potentials results often with incomplete analytical results, which imply incomplete information for business decisions and can imply bad business decisions. The chapter also provides suggestions on how to recognize useful data sources from the big data area and how to analyze them along with traditional data sources for achieving more qualitative information for business decisions.

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