Big Data Analysis using Weka Machine Learning Program and SPSS Package: A Comparative Study

Abstract

Companies are currently rich in huge amounts of data but are weak in information extracted from data. This massive data is a valuable resource. Although the concept of big data is still new, many international companies are relying on it to make strategic decisions. This study examined the regression analysis, which is part of Multivariate Analysis, which was an implemented step method on real data and the efficiency of the regression analysis when increasing the size of the sample tested, The importance of this study is to compare the method of statistical analysis, keep in mind the optimal use of available resources in computers such as Random-Access memory (RAM) and processor speed to reach the results to be the best in terms of time spent on analysis after confirmation of the validity of the steps involved in getting the prediction. The study used the descriptive statistical approach to describe the study variables, and the analytical statistical approach to obtain the study results using the SPSS20, WEKA programs. The aim of the study was to make a comparison between the WEKA program indicators and the SPSS package to determine which of them is efficient in large samples. The study concluded that using WEKA software because gives better results than using SPSS program. And Increasing the sample size increases the efficiency of the WEKA program indicators compared with the SPSS program indicators when large samples. The study recommends to using the weka program in the case of large samples because it is more efficiency in prediction parameters compared with the SPSS program indicators in the same parameters.