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Descriptive and Predictive Analytical Methods for Big Data

Descriptive and Predictive Analytical Methods for Big Data

Sema A. Kalaian, Rafa M. Kasim, Nabeel R. Kasim
Copyright: © 2019 |Pages: 18
ISBN13: 9781522575016|ISBN10: 1522575014|EISBN13: 9781522575023
DOI: 10.4018/978-1-5225-7501-6.ch018
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MLA

Kalaian, Sema A., et al. "Descriptive and Predictive Analytical Methods for Big Data." Web Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 314-331. https://doi.org/10.4018/978-1-5225-7501-6.ch018

APA

Kalaian, S. A., Kasim, R. M., & Kasim, N. R. (2019). Descriptive and Predictive Analytical Methods for Big Data. In I. Management Association (Ed.), Web Services: Concepts, Methodologies, Tools, and Applications (pp. 314-331). IGI Global. https://doi.org/10.4018/978-1-5225-7501-6.ch018

Chicago

Kalaian, Sema A., Rafa M. Kasim, and Nabeel R. Kasim. "Descriptive and Predictive Analytical Methods for Big Data." In Web Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 314-331. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7501-6.ch018

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Abstract

Data analytics and modeling are powerful analytical tools for knowledge discovery through examining and capturing the complex and hidden relationships and patterns among the quantitative variables in the existing massive structured Big Data in efforts to predict future enterprise performance. The main purpose of this chapter is to present a conceptual and practical overview of some of the basic and advanced analytical tools for analyzing structured Big Data. The chapter covers descriptive and predictive analytical methods. Descriptive analytical tools such as mean, median, mode, variance, standard deviation, and data visualization methods (e.g., histograms, line charts) are covered. Predictive analytical tools for analyzing Big Data such as correlation, simple- and multiple- linear regression are also covered in the chapter.

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