TIM-8530 v5

Khattak, W., Buhler, P., & Erl, T. (2016). Big data fundamentals: Concepts, drivers, & techniques.Pearson.
Read Chapter 8 – Big Data Analysis Techniques.
This chapter describes the various types of analyses conducted with big data, including quantitative, qualitative, data mining, statistical analysis, machine learning, semantic analysis, and visual analysis.

Dasgupta, N. (2018). Practical big data analytics. Packt Publishing.
Read all sections from Big Data Mining for the Masses to Summary.
These sections discuss the use of big data mining in the enterprise to build insights. Topics covered include making a case for a big data strategy, implementation of the lifecycle, and the stakeholders of the solution.

Banchhor, C., & Srinivasu, N. (2021). Analysis of Bayesian optimization algorithms for big data classification based on Map-Reduce framework. Journal of Big Data, 8(1), 1–19.
This journal article describes the process of big data handling during the use of a classification algorithm and a naïve Bayes classifier (CNB).