Reaction: Effectively Communicating Numbers

The paper starts with a scenario and assessing different visualization types suitable for the scenario. Selecting an inappropriate visualization results in miscommunication of data. Quantitative data is not
easy to communicate and therefore the paper gives 6 stages to use graph visualization for them.

The author then tries to introduce the following concepts:

1. General concepts of tables, graphs, handling categorical data.

2. Relationships in quantitative business data. These relationships have a great effect on the type of visualization used as one may effectively convey the relationship better than the other.

3. How to use graphs to encode data.

The white paper gives guidelines to:

1. Identify important data within the dataset to be visualized.

2. Determine if a table, graph, or combination of both is needed to communicate your message.

3. Determine encoding by determining the relationship in data.

4. Associate variables to the data in case of axes, using color schemes to differentiate data. Also the article gives guidelines to represent other peripheral data critical to associate meaning to the representation.

This paper will force the users to think and analyze their quantitative data before they choose a visualization to represent the data or use tables or text. I think the 6 steps given are fairly comprehensive. Also, the techniques will help to represent the data more clearly and highlight the important data.