Book Image

Data Visualization: a successful design process

Book Image

Data Visualization: a successful design process

Overview of this book

Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories and key insights locked away."Data Visualization: a Successful Design Process" explores the unique fusion of art and science that is data visualization; a discipline for which instinct alone is insufficient for you to succeed in enabling audiences to discover key trends, insights and discoveries from your data. This book will equip you with the key techniques required to overcome contemporary data visualization challenges. You'll discover a proven design methodology that helps you develop invaluable knowledge and practical capabilities.You'll never again settle for a default Excel chart or resort to "fancy-looking" graphs. You will be able to work from the starting point of acquiring, preparing and familiarizing with your data, right through to concept design. Choose your "killer" visual representation to engage and inform your audience."Data Visualization: a Successful Design Process" will inspire you to relish any visualization project with greater confidence and bullish know-how; turning challenges into exciting design opportunities.
Table of Contents (13 chapters)
Data Visualization: a successful design process
About the Author
About the Reviewers

Data visualization methods

The common definition for taxonomy comes from the biological sciences and refers to the organization into groups of members that share similar characteristics. In this case, the members are chart types and the shared characteristic is based on the primary data portrayal function.

Selecting the appropriate visualization method will be influenced by the definition work you undertook earlier in the methodology to clarify the intention of your visualization communication.

It is about starting the journey towards identifying the most suitable way to answer your main data questions: how are you going to show, what it is you want to say.

Here is an outline of the primary communication purpose of each method classification:

Method classification

Communication purpose

Comparing categories

To facilitate comparisons between the relative and absolute sizes of categorical values. The classic example would be the bar chart.

Assessing hierarchies and part-to-whole relationships...