INTERACTIVE DASHBOARD FOR USER ACTIVITY USING NETWORK FLOW DATA

Abstract

Data visualization is critical in analytical systems containing multi-dimensional dataset and problems associated with increasing data size. It facilitates the data explanation process of reasoning data and discovering trends with visual perception that are otherwise not evident within the data in its raw form. The challenge involved in visualization is presenting data in such a way that helps end users in the process of information discovery with simple visuals.

Interactive visualizations have increasingly become popular in recent years with prominent research in the field of information visualization. These techniques are heavily used in web-based applications to present myriad forms of data from various domains that encourage viewers to comprehend data faster, while they are looking for important answers.

This thesis presents a theme for visualizing discrete temporal dataset (pertains to network flow) to represent Internet activity of device (interface) owners with the aid of interactive visualization. The data presentation is in the form of web-based interactive dashboard with multiple visual layouts designed to focus on end user queries such as who, when and what. We present "event map" as a component of this dashboard that represents user activity as collections of individual flow from the dataset. In addition, we look into design issues, data transformation and aggregation techniques involved in the narration of data presentation. The outcome of this thesis is a functional proof-of-concept, which allows demonstration of a network flow dashboard that can be served as a front-end interface for analytical systems that use such data (network flow).