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A solution approach to big data regarding parameter estimation problems in predictive analytics model

Author Affiliations

  • 1Department of Computer Science and Applications, Dr. Harisingh Gour Vishwavidyalaya India
  • 2Department of Mathematics and Statistics, Dr. Harisingh Gour Vishwavidyalaya, India

Res. J. Computer & IT Sci., Volume 8, Issue (1), Pages 1-8, June,20 (2020)

Abstract

The existence of big data is everywhere because of social media and business organizations move forwards into online services. Big data is not just a considering volume of data, it is a concept which explains about the gathering, organizing, analyzing the data and extract information from those data sets. Big data analytics concept used in our daily life for various purposes such as weather forecasting, market trends and deals with heterogeneous data. The problem of parameter estimation in big data may be looked upon into three aspects volume, variety and velocity which are known as 3Vs. In big data environment, the users are receiving and sending variety of data (text, images, videos) over the Internet due to it is a challenging task to process and getting valuable solution with minimum data processing speed. In this paper we have picked big data parameters estimation problem and proposed a prediction model to estimate big data parameter based on sampling estimation technique. The model is applicable on dynamic nature dataset. In our proposed method we have applied stratified random sampling techniques for estimate those unknown parameters and compare the result with another sampling techniques.

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