Multidisciplinary Data Visualization

Data Visualization is a key aspect of modern day life. With the ever increasing use of technology to organise and arrange our lives from simple decision making such as what meal to order to at a restaurant to complex long term decisions such as which mortgage is best for you, the need for efficient and precise data visualization has become essential. The task of data visualization systems is to assist with the easier human visual processing of large amounts of data which has multidimensional connections. This is especially important in industry, where key decision makers must get data presented to them in ways that are easy to understand. Although raw data itself is obviously a key part of data analysis, it is almost always unstructured and difficult to comprehend, even after analysis is carried out conclusions and connections between pieces of data may not always make sense to outside viewers without a concise form of visualization.The purpose of this book to highlight the importance of data visualization, to discuss the methods and techniques available for data visualization and to provide a variety of concise examples demonstrating the power and usefulness of data visualization. The book should be useful for people with diverse interests - from laypeople to the topic of data visualization to everyday practitioners as well as to professional data scientists.This book starts off with a gentle introduction to data visualization, highlighting the importance and the relevance of data visualization. The question of why we must embrace data visualization is answered. Data visualization is an art as well as a science. The book is dedicated to explaining this in detail. Key elements of good visualizations are discussed. The art of choosing the charts, the colors and the shades to decorate the visualizations are discussed in detail. There exist very many methods and techniques for data visualization. The book highlights the common methods and techniques for data visualization - ranging from simple charts to complex maps. The aim here is to expose to the reader the depth and breadth of the methods and techniques that are available. Equally, the reader will be exposed to the varieties and types of software tools available to create visualizations. A crucial part of this book is to provide numerous multidisciplinary examples. A whole chapter in this book is dedicated to delivering multidisciplinary data visualization examples from a wide variety of backgrounds. Reading and understanding these examples will help the user to appreciate the mindset and the methodologies one must adopt in tackling significant data visualization challenges.