5Ws Model for Big Data Analysis and Visualization
Jinson Zhang, Mao Lin Huang · 2013
Big Data, which contains image, video, text, audio and other forms of data, collected from multiple datasets, is difficult to process using traditional database management tools or applications. In this paper, we establish the 5Ws model by using 5Ws data dimension for Big Data analysis and visualization. 5Ws data dimension stands for, What the data content is, Why the data occurred, Where the data came from, When the data occurred, Who received the data and How the data was transferred. This framework not only classifies Big Data attributes and patterns, but also establishes density patterns that provide more analytical features. We use visual clustering to display data sending and receiving densities which demonstrate Big Data patterns. The model is tested by using the network security ISCX2012 dataset. The experiment shows that this new model with clustered visualization can be efficiently used for Big Data analysis and visualization.