The Delivering Data Chapter was very insightful on ways to present data. I have always said that beautiful visualizations are much more meaningful than words on a page. Even my example in a previous blog post for this class proved this exactly. The data I had gathered about terrain for Colorado ski slopes was in percentages, you can read down the list, and maybe after spending ten minutes looking at the data you could see which slopes are the easiest, or the hardest. But the chart I created showed this in a matter of seconds, mainly because people are much more drawn to visual creations.
I think some of the best visualizations are those that the user can interact with personally. For example, data visualizations that let a user customize the data to something that is relatable and relevant to them. For example, when using your own zip code to see how something relates to your city, or picking your own doctor for the dollars for docs project.
The tips for analyzing your data were very helpful. If you publish incorrect data that could have otherwise been prevented by thorough proofreading, it could haunt you, and quite frankly be embarrassing.
For one way to present my data, I was thinking of doing a chart appearance similar to this below, but with a different representation obviously. Since my topic is on Colorado skiing, I think it would be cool to use the elevation data of the mountains from highest to lowest and color code it from expertise levels (beginner, intermediate, advanced, and expert) for each Colorado ski resort/mountain.
