A Statistical Computational Method for Predicting Storage Capacities in the Big Data Era

In the digital era, where everyone continuously generates massive volume of data with different origin like social media-based applications, healthcare, transactions, e-commerce, etc. Such data needs a large space to be stored permanently which can be used in the present or future to make the decision. Big data have the potential value to make needful decisions in the area including business and Government policy implementation. The decision-making process involves various tools and technologies to predict meaningful insights. Such types of tools are used in the statistical method to predict things. Statistics in machine learning play a vital role in developing a prediction model. This paper has presented a statistical method for digital file size estimation in a big data environment. The suggested method is capable of predicting the storage capacity of the data center for a variety of files like text, images, video, etc. The 95% confidence intervals, which help identify the unknown value, are calculated through a simulation process.