Data visualization, also known as “data viz”, is an interdisciplinary field that deals with the graphic representation of data and information. Wikipedia says: “Data and information visualization has its roots in the field of statistics and is therefore generally considered a branch of descriptive statistics. However, because both design skills and statistical and computing skills are required to visualize effectively, it is argued by authors such as Gershon and Page that it is both an art and a science.”
Numbers help us understand performance and make decisions. Time spent learning how to properly present information is time well spent because for those looking at the data, a proper presentation will save them time.
A good data visualization should be able to communicate what you are trying to convey within 5 seconds. Data visualization is the intersection or art and analytics. Also, a lot of people associate green with positive results and red with negative results.
Exploratory vs. Explanatory Data Analysis
Are we looking to explore the data to glean insights, or have we found a few insights that we need to communicate to others? The first is exploratory and the second is explanatory. Our data visualizations will be different in either case. Exploratory data analysis is like sending people into a forest with the best compass that you can devise. Exploratory data analysis is like hunting in the forest. While storytelling is more like leading them along a previously marked out trail. Are you looking for patterns or are you communicating patterns?
Excel
Microsoft Excel has a lot of charting features.
Tableau
The software called Tableau specializes in data visualization.
Five Free Data Visualization Tools
- Tableau Public
- Google Charts
- Datawrapper
- D3 (Data-Driven Documents)
- RAW Graphs
Choosing the Right Chart
Have a look at this YouTube video called Which is the best chart: Selecting among 14 types of charts Part I. Which is the best chart: Selecting among 14 types of charts Part II. Here is a post I have here called Choose a Visual Display. It’s part of a series of blogs based on the book by Cole Nussbaumer Knaflic called Storytelling with Data.
Learning with Blogs and Websites
What are some of the best blogs to follow to learn more about data visualizations? Here’s a post from Tableau called The 10 Best Data Visualization Blogs To Follow.
Data Visualization for Human Perception. Data Visualization Gallery (US Census). Income of Registered Nurses (RNs). Junk Charts. These are poor, bad charts at this website. Here’s another websit. The Surprising History of the Infographic by the Smithsonian. Mr. Hunter Whitney at UX Magazine.
Resources
What are the best resources for learning data visualization?
- Tableau Public. Tableau offers a comprehensive education and tutorial platform focused on training both software users and class leaders? Check out the Resources tab.
- Power BI. They provide comprehensive guided learning and online workshops
- Information is Beautiful. Founded by author and data visualization expert David McCandless, the Information is Beautiful platform is a gathering place for data pros who want to help people make clearer, more informed decisions in the world.
- Storytelling with Data. Storytelling with Data is an organization focused on communicating with concise data that informs change. They provide training, workshops, and tools.
- Python Graph Gallery. This Python Graph Gallery site created by Yan Holtz includes a wide range of different types of visualization plots, like bar graphs, line charts, times series charts, geographic maps, and many more. The site is organized first by plot type, but can also be sorted by the visualization Python package used, seaborn, matplotlib, or plotly.
Here is a link to some infographics that show how Microsoft stacks up against Apple, Google, and Amazon. These are really impressive. They show the source of revenues and the types of expenses that these companies incurred. Very easy to read and understand. The article is at Windows Central.