Over the last seven weeks, I took a deep dive into the world of Dataviz as a part of my Master’s program. Although I will be shifting my focus away, for now, I know that I will be carrying new knowledge with me to my future learning endeavors. So many pieces of what I have learned can be translated (and already have been) to my real-world professional experiences. Researching, ideating, exploring new software, and drawing has all been incorporated into the last seven weeks in ways that I have not practiced in the past. All of these techniques come together to create successful data stories.
In the last few weeks, specifically, I worked on my own data story in Tableau, which can be found here on the Tableau Public site. In the text to come, I go through my experience creating this story and how I applied my new knowledge to make it effective.
Data
First comes first in any data visualization. And first is, of course, the actual data. Of all the topics covered in this DataViz class, I have to say I had the hardest time with the data. This sounds silly considering the whole topic of the course is data. However, in my real-world experience, I have never had to research and clean my own datasets. They have been handed to me neatly and organized so that I could simply design them and “make them pretty.”
Over the last 7 weeks, I learned that in order to create an effective visualization it is important to be active on the back end of the design. To be a good designer means knowing the meaning and purpose of what you are creating. Sometimes, that means doing your own research or at least being involved in it.
Finding the datasets that were used in my Tableau story probably took me way longer than it should have, but through the frustration, I was able to learn something new. I am no longer only skilled in making something look presentable. I am now skilled in being able to create my own story out of substantial data.
Storytelling
Ideation has been a recurring theme throughout my schooling. When I applied it to data visualization in recent weeks, I was able to look at it from a new angle. Typically, I would use ideation for a big picture job. Maybe a website/app layout, or a bigger campaign. For my Tableau data story, I was challenged to scale my ideation down. I had to take my abundance of research and think of a way to put it together to create a purposeful story. In the end, I achieved the clarity I needed by scaling down and getting rid of excess data. By cleaning out all of the extra junk I was able to find connections between each of my data spreadsheets. I found myself using brain dump and mind mapping techniques in order to get a cohesive storyline in the works.
In the end, I had a six-slide story in Tableau.
Slide 1 – An Upward Trend in Organic Food Sales
Slide 2 & 3 – How does our organic farmland acreage hold up to our inorganic?
Slide 4 – What does this organic acreage shortage mean to the consumers?
Slide 5 – Why is there a shortage of organic farmland despite rising popularity?
Slide 6 – What is being done to help the issue? How can we help?
These 6 slide topics were enough to get my message across and leave the audience with an opportunity to take action by the end.
Visuals
Learning about the visual aspect of DataViz is something I have very much enjoyed over the course of this class. It is also something I have already been able to apply to my current job. Having been designing and laying out a research report for work at the front end of this course, it served as a great test for my new knowledge. I was challenging myself on what charts and graphs I was choosing to create for the project. “What visual makes the most sense for the story being told?”
The class text, Good Charts, has been a great reference guide in creating charts and graphs inside and outside of class. While in Tableau and throughout the creation of my data story I was sure to ask myself whether my charts were persuasive or manipulative. In my first Tableau slide, we take a look at the sales growth of organic foods. Although tempted to truncate the Y axis to make the trend look steeper, it is important to gain the trust of your audience. Persuasion over manipulation.
Visually, we use size, color, and shape as ways to display certain chart elements. As in the maps shown in slide 3 and 4 of my data story, the variance in organic and inorganic farmland can be seen clearly through a range of color and bubble size. Not much reading or inspection is necessary.
When combining numerous charts into one cohesive story, as in my Tableau story, it is important to keep all of those same elements throughout. By doing this we keep consistency and create momentum with our storyline.
Conclusion
Learning and reading about data visualization from a new perspective has changed the way I think about my work and my designing. Taking a look at the data behind the visual helps you make smart choices when it comes to how you display your information. When you switch gears to focusing on the visuals, you can use graphic elements to drive your message home and to make an impact. Utilizing both sides of DataViz is where success is found.
Samantha Mantiglia 