Graph Analysis and Visualization
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Graph Analysis and Visualization

Discovering Business Opportunity in Linked Data

Richard Brath, David Jonker

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eBook - ePub

Graph Analysis and Visualization

Discovering Business Opportunity in Linked Data

Richard Brath, David Jonker

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About This Book

Wring more out of the data with a scientific approach to analysis

Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book.

Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers.

  • Study graphical examples of networks using clear and insightful visualizations
  • Analyze specifically-curated, easy-to-use data sets from various industries
  • Learn the software tools and programming languages that extract insights from data
  • Code examples using the popular Python programming language

There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.

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Information

Publisher
Wiley
Year
2015
ISBN
9781118845875
Edition
1

Part 1
Overview

The first part of this book introduces the subject of graphs and provides answers to two essential questions: why are graphs valuable to business analysis, and what kinds of opportunities can they be used to discover? A wide spectrum of techniques and applications are discussed, drawing from history and real-world experience. Case examples are used to illustrate value.
Before proceeding to a discussion of the process of graph analysis in the second part of the book, this overview provides you with a sense of just how many types of graphs there are and how many areas of potential value exist, even within a single business. References serve as a guide to subsequent chapters in the third part of the book, which cover each class of graph in more detail and step through tutorial style applications of graph analysis.
Table P1-1 describes the topics of Chapters 1 and 2.
Table P1-1: Overview
TopicDescription
Why Graphs? (Chapter 1)
p01g001.tif
What are graphs, and why are they useful to a business analyst? Chapter 1, “Why Graphs?,” introduces the concept of graphs, and defines several key terms used in this book. Select historical and modern anecdotes recount applications of graph analysis and visualization in business, documenting a steady rise to prominence spurred on by today’s challenges of vast and complex data. Real-world cases attest to the value of graphs.
A Graph for Every Problem (Chapter 2)
p01g002.tif
Chapter 2, “A Graph for Every Problem,” provides a systematic overview of the wide variety of graph types and the kinds of problems they are useful for solving. The discussion begins with an example contrasting how relationships revealed in other ways can also be expressed using nodes and links. Subsequent topics describe graph techniques for gaining business insights involving hierarchies, communities, flows, and spatial networks. References are included to further detail in subsequent chapters.

Chapter 1
Why Graphs?

This book is about graphs and how graphs can be used to help solve business problems. When many people hear the word “graph,” they think bar charts or line charts, and rightly so, because those are also sometimes known as bar graphs or line graphs. This book is not about charts. This book is about the node-link diagram kind of graph.
At its essence, a graph is a structured representation of connected things and how they are related. As you will discover in the following chapters, graphs are capable of representing complex data in a way that an analyst can make sense of.
Because graphs have a long history in mathematics, discussions about graph analysis and visualization tend to include a lot of confusing esoteric terms such as edge and degree. This area of study responsible for this is generally known as graph theory.
For the discussions in this book, we use more universally accessible and less ambiguous terms where possible. For example, a link is a relationship between nodes and is typically drawn as a line. Nodes are entities (or essentially “things”) that are joined by links. Nodes are often represented visually by a circle.
An edge is another word for a link in graph theory, and the term degree becomes a little less opaque if you are familiar with the concept of six degrees of separation, popularized by the play and movie of the same name. But only a little less opaque, because not only can “degree” mean the minimum number of steps of separation between linked entities, it can also mean the number of link connections that a node has.
Note
The glossary at the end of this book can serve as a cheat sheet if you find you need a little graph-theory-to-English translation.
In some circles, graphs are still viewed as abstract and difficult-to-understand constructs used mainly by scientists walking around with disheveled hair. Although graphs do have a long-standing tradition in scientific circles, the reality is that, when properly designed and executed, graphs can be one of the most intuitive ways to analyze information. There is a good chance you have used graph representations if you drew things in a notebook or on a whiteboard to think through or explain concepts—which is really a form of visualization.
More importantly, graphs provide a means of gaining highly unique and valuable insight from data. Graph analysis brings complex relationships to light, informing effective decision-making. Visualization is central to that process. Being able to see relationships visually is critical to understanding, whether they be characteristics of the raw data or specific features highlighted by graph analytics.
Information visualization exists for the sole purpose of understanding more, and in less time. Our brains are naturally wired to perceive and comprehend things visually. Reading is a time-consuming, sequential process, requiring the reader to mentally piece together an understanding. Pictures can convey information instantly, revealing complex patterns and outliers in easily digested ways.
There was a time when visualizations were drawn by hand after the painstaking gathering of data. But today, computer systems can harvest vast amounts of data and turn it into pictures in mere milliseconds, enabling analysts to instantly comprehend and act on information. Virtually any business can now benefit from visualization, and, as a result, it has become core to systems across all industries and around the world. Graphs, however, are one of the last forms of visualization to remain underutilized. There was a time, though, when that was true for all information visualization in business.

Visualization in Business

The use of computer-rendered visualization for decision-making in business is a relatively recent phenomenon. Twenty years ago, as recent grads from the University of Waterloo School of Architecture, we decided to abandon the design of physical landscapes for the lure of an emerging and wide-open new world of virtual landscapes. One of us spent a few years working on three-dimensional (3-D) modeling software before we joined forces with other colleagues to see if similar technology could be applied to the problem of displaying large amounts of abstract information for high-flying decision-makers in finance and other industries. The seeds of that collaborative venture were to grow into an eventual long-term partnership, which included William Wright and another young architect, Thomas Kapler.
In the early days of this venture into business visualization, the value of even primitive charts was not always widely understood or accepted in offices of Fortune 500 companies. Our first pitches to corporate decision-makers started with the most basic of value propositions—that of the value of visualizat...

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