Preprocessing data in big data analytics (a survey) - S. T. M. Poovarasi, J; Srinivasan, Sujatha (International Journal of Engineering and Technology, 2018)
Big Data is a large amount of data with various types of data. Big data analytics (BDA) is to uncover a hidden pattern of data, its unknown correlations, observe the market and customer needs and also other information which helps organizations to make right decisions on busi-ness. With today's technology, big data is analyzed and immediately solutions are generated. The effort taken does not provide effective business solutions. It makes the process slow and gives the less efficient intelligent solution which does not provide what the business mar-ket needs. With existing Big Data analytics (BDA) techniques and tools it is not possible to process quickly and efficiently since these are incapable of dealing with mega amount of data. The knowledge and pattern from Big data analytics (BDA) are sometimes inaccurate. Thus the data requires some preprocessing like aggregation, sampling, normalization, in order to save data in the memory locations of a computer and analyze it. This study gives a short review of the preprocessing techniques for Big Data.Â Â Â