누구나 사용할 수 있는 분석 도구
누구나 사용할 수 있는 데이터 준비 도구
조직을 위한 분석
조직을 위한 클라우드 분석
Have you ever found yourself staring at a blank Tableau canvas, unable to start a viz? I have. From vizzer’s block to being paralyzed by choice, I know that gray canvas well.
This week, I found myself in a familiar situation. I had a great food-survey data set, bursting with stories waiting to be told but where should I start(1)? Thankfully, I have a few tricks to help overcome the blank-canvas blues.
Drawing/sketching/doodling (whatever you want to call it) is one of the best forms of brainstorming I know. The sketches don’t have to be pretty or even legible. Putting pen to paper is my best way to kickstart the creative process.
One of the best ways to be inspired is to surround yourself with inspiring people and vizzes. For me, this means following data vizzers and data journalists on Twitter, reading data-viz books, and taking notes (or screenshots) of vizzes I like.
This tactic paid off. I came across this visualization by the Washington Post, and immediately saw how I could make a similar viz to tell my food-survey story.
It might sound counterproductive to get your creative viz juices flowing by following a checklist, but structure can help overcome vizzer’s block. My checklist is divided into two parts, data preparation, and data exploration.
As dull as it sounds, physically looking at your data helps you understand the data set’s possibilities and limitations. Here are some of the things I look at in a data set:
By going through this list, I could see that my food-survey data set had multiple levels of details in it—some food had up to four sub-categories while others only had two. That meant it would be hard to meaningfully compare two food items unless I knew that they were both at their lowest sub-category.
I think of analyzing a data set as a way of interviewing it. If I’m stuck staring at a blank Tableau canvas, I can fall back on asking traditional interview-style questions of my data:
Here's one line of questions I asked of my data:
As you can see, interviewing your data gives a structured way to beat the blank-canvas blues.
Sometimes I find myself unable to start vizzing because I’m worried that the final viz won’t show the deepest insight, or won’t be the best way to tell the story. Remember that there are an infinite number of ways to approach a viz, that there isn’t only one best story to tell with a viz nor a best way to tell it. Lastly, once a viz is finished, that isn’t the end. As projects like Makeover Monday show us, once a viz has been made, you can continue to remake it and tell stories with it in different ways.
When I really need to focus, I crank up the tunes. Reducing the sound of outside distractions (phone buzzing, colleagues talking, TV blaring) helps me focus on my work. Whatever your favorite kind of music, get some headphones and let it blast! For reference, Dvorak’s New World Symphony (No.9) got me through writing this blog post.
Here's the viz I finished after beating the blank-canvas blues.
1 In this particular instance, I had a fabulously rich data set from the UK Family Food Statistics. I knew this data set had some great stories to tell from articles such as The ODI’s “How British diets have changed since 1974” and The Guardian’s “Goodbye, fish and chips: National Food Survey data reveals changing trends in British dining”. I also looked at this data set at the London Viz Club. But sometimes too many options is as bad as too few; I was paralysed by choice.