Deriving Big Data insights using Data Visualization Techniques

Abstract

Exponential growth rate in the data generation in diverse fields revolutionized the way the analytics tools and machine learning algorithms applied in the Big Data. Considering the pace at which data is generated and the variety of data, identifying the right data at the right time and the relationship is crucial to make decisions. Identifying the data type and the relationship between the parameters is challenging as the size of the real time data is massive and dynamic in nature. Data Visualization as part of Big Data Exploratory analysis helps to identify the relationship and to understand the characteristics of big data in an effective way. In other words, data visualization is the graphical representation of data, it links the data availability and data analysis, organizes and presents important findings from the data. As plenty of visualization packages and tools are available, choosing the right tool is very important. gglot2 is one among the statistical graphics tool for data visualization as the working model is entirely based on grammar of graphics. The unique feature of ggplot is the layered approach, as the each component is highly interdependent on the other and so it helps in the step by step analysis of the data. With this feature available ggplot2 was used in the Real time Public Distribution System data to identify the relationship between various parameters and to understand the behavior pattern.