Graphs are one of the most versatile and powerful ways to express complex data—and the least understood. In reality, people use graph techniques in meeting rooms every day, labeling and diagramming relationships to explain their thinking to others. Graphs can express relatively complicated concepts that other visualizations cannot.
When chosen wisely, the right technique can lend the simplest and most intuitive expression of a particular type of information. When chosen poorly (or naively employed), a graph can be painfully abstract and obtuse. One of the primary goals of this chapter is to encourage graph authors to break free of the trap of simple colored nodes and links and to think more creatively about graphs.
This chapter introduces graph solutions and is organized by classes of problems. Later chapters in Part 3 of this book provide in-depth walkthroughs of each of these classes using example problems and data. Documented, reproducible steps are provided for using tools, and sometimes code, to do the same.
At first glance, your own business problems may seem too multidimensional to fit into one of these seemingly small and tidy boxes. For example, your problem may involve both spatial networks and flow and will certainly always involve relationships. These are not mutually exclusive aspects. When choosing an approach, try to think of what is most fundamental about the questions you are attempting to answer.
One of the ...