#SURGVIZ

Bringing visual storytelling to surgical education and research.

Step 2: Download Workbook — April 12, 2017
Data Viz Intro —

Data Viz Intro

Data visualization or “data viz” is the process of creating a visual representation of any type of data. The practice is often called information design and the tools are important for visual analytics.

If you are a data viz newbie, a great starting point on the topic is the Duke Library guide on Data Visualization. They even have a thorough list of Dos and Don’ts to be aware of when designing and communicating visual data accurately.

More Posts about Data Viz:
Infographics
Choosing the Right Data Viz

Software:
About Tableau
Download Tableau Public
Learn the basics
R Packages

Keim06visual-analytics-disciplines
[Keim et al., 2006] Keim, D.A.; Mansmann, F. and Schneidewind, J. and Ziegler, H., Challenges in Visual Data Analysis, Proceedings of Information Visualization (IV 2006), IEEE, p. 9-16, 2006.
Welcome! — April 11, 2017
Choosing the Right Data Viz — April 9, 2017

Choosing the Right Data Viz

Determining the optimal way to visualize your information depends on what type of data you have. And scatter plots and bar graphs are not the only option.

So how do YOU make something like this for your data? The first step is to understand the results of your data and decide the purpose of your visualization.

Then, you need to figure out the advantages and disadvantages of each type of visualization. Not all of them are going to be appropriate to present your data. The following sites describe the advantages and disadvantages well:

chartopedia
Chartopedia is an information resource with a nice clean visual dictionary of many different types of charts.

Source: Chartopedia | AnyChart

 

 

The Chart Chooser below is a Tableau Public workbook that helps users chose what type of chart they need for their purposes.

Chart Chooser

Step 1: Download Tableau Public — April 7, 2017
More Tableau Practice and Learning — April 1, 2017

More Tableau Practice and Learning

If you’ve already visited our Learn the Basics page, then take the next steps to improve your Tableau skills: find a community, gather inspiration and get more practice with hands-on experience and feedback. If you want more structure, there are also several courses we can recommend.

Find a community

twitter pink2Share your Tableau or data viz creations and help us start our own #SurgViz community! Find us on Twitter (@SurgViz).

Gather inspiration

pinterest pinklCheck out our Pinterest page for lots of boards on data visualization, infographics, graphical design, and more.

Get more practice

For the surgeon looking for more hands-on practice, there is a whole data viz community you can tap into for inspiration and help:

#MakeoverMonday — (Great for extra practice and getting inspiration)

Every week, this social data project posts a figure and a data set that needs some improvements. Across the globe, data viz neophytes and experts try to rework the visualization using Tableau.  The community shares their creations on Twitter and on an impressive Pinterest board.

#TableauTip Tuesday — (Good for learning specific tricks quickly)

This is an awesome list of tips and tricks posted weekly by one of the Tableau Zen Masters. They feature screenshot breakdowns, workbooks to download, and occasionally short video explanations.

data+science also has a thorough Tableau Reference guide. They have compiled and organized long lists of how-to guides by top Tableau viz experts and Tableau “Zen Masters.”

Take classes

See a list of popular courses here.

High Yield YouTube videos:

Tips and Tricks for Beginners (40 minutes)
The tips in this video will save you time down the line and had information I wish I had a year ago.

20 Quick Design Tips for Tableau Dashboards (14 min)
the video is only 14 minutes but it provides a great before and after example of how just some small changes can make a dramatic visual difference.

How to Design Engaging Data Stories in Tableau (40 min)
A member of Tableau’s sports visualization team goes over the 7 main types of stories you can tell with your data.