Pruning Deficiency of Big Data Analytics using Cognitive Computing

Abstract

Since past few years the size of the data is growing extremely at fast rates 10 times faster in growth. This will include all the responsibilities to make smart decisions streaming from the browsing patterns and produce extra supplements which aids in the decision-making progress. As the size of the data is recorded from a variety of devices like mobile sensors, remote sensing and data is recorded from everywhere; huge amount of data gets stored which is sometimes even never analysed. Big data is a very “big” thing which is getting stored and increasing the volume of raw data sometimes 90% of the raw data sets are never analysed and are just discarded from the memory. Out of it just 10% gets analysed sometimes and are converted into information from those raw data sets. So, analysis of data by human beings could be time consuming but processing enormous amount of data at a large scale using cognitive can be done. In this paper, we tried to focus on the areas where the cognitive computing can be used in order to lessen the shortcomings of the big data analytics, principles from which cognitive computing came. We also focused on the urgent need on how the language processing of data is done to understand the meaning of the rough data and process it to useful information.