The Makeover Monday Community never ceases to amaze me! What a week! A really simple data set, yet way over 250 different visualisation. You all inspire us! There’s a lot to cover this week, so let’s get to it.

 

MAKEOVER MONDAY LIVE!

Eva and I ran separate Makeover Monday Live event this week. Eva was in Helsinki while I was in San Diego. We absolutely love running these and introducing people to MM and the benefits it can provide to their career.

If you’d like us to host an event near you, give us a shout!

 

LESSON 1: EVEN THE BEST DON’T GET IT RIGHT ALL THE TIME

This week, Zen Master Chris Love tried something new and created a world tile map.

Almost immediately after posting his work, Chris got lots of questions about exactly what he was trying to communicate. Things like:

  • “What value does land mass add?” ~Adam McCann
  • “I didn’t recognize you were going for a map.” ~Jeffrey Shaffer
  • “I think if you put a sea monster and a compass rose in the negative space it would clarify things tremendously.” ~Mike Cisneros

Here the catch though, failure is the best way to learn! Chris didn’t take the feedback personally, he wasn’t offended. He created a viz that he thought worked and it didn’t. We’ve all been there and we’ll be there again. What’s great about Chris is he can accept the feedback and iterate. Chris landed on a simpler viz.

The point here is that a visualisation is never “done”. It’s ok to iterate. It’s okay to ask for feedback, and you only get better by iterating on that feedback as Chris has done.

 

LESSON 2: GEOGRAPHIC DATA DOESN’T MEAN YOU NEED A MAP

The simplicity of creating a map in Tableau makes you want to create maps. That little globe icon is tantalizing. One of the major problems with the original viz was the filled map. You simply can’t see smaller countries.

Even when you zoom into Europe, it’s hard to pick out the tiny countries.

My advice: if you create a map, step back from your computer 5 steps. Can you still see the difference in the countries? If so, you’re good. If not, try something else.

 

LESSON 3: ACT LIKE AN ANALYST

If you want to be great at data analysis, you have to practice, you have to be able to find insights in the data, you have to explore the data, you have to communicate your findingS well. This week, Charlie Hutcheson demonstrated this perfectly. He explored the data, found some insights, then used his data visualization and storytelling skills to communicate it succinctly, clearly, and simply. SIMPLE IS HARD!

 

LESSON 4: LEARN HOW TO TELL STORIES WITH DATA

Storytelling is part of being a data analyst. Often it can be thought of as data journalism. How can you take a data set and communicate a data story? This takes practice, lots and lots of practice. Two people this week told incredible data stories.

In this viz, Mike Cisneros, one of the best in the business, essentially told a news story. He let’s the user pick the story they want to see and the viz updates according to what they choose. Amazing work Mike!

Much like Mike, Jeremy Kneebone found a story in the data, then used his data visualisation skills to explain the story to the reader.

Jeremy, who is currently in training at The Data School, used color, divider lines and annotations to walk the reader through the story. This takes time and taking this time results in a better experience for the reader.

 

LESSON 5: AGGREGATING DATA THAT CAN’T BE AGGREGATED

This is the only rather negative lesson this week. I saw too many vizzes this week like this one:

In this example, I’ve stacked the genders and I’ve included all countries. I know I saw at least 10 people create something similar this week. Ask yourself, are people now living 140+ years? Of course not! Sense check your visualisation. In addition, people were averaging together the averages of all of the countries. That’s flat out wrong! You have to account for yearly population to do that.

Think. That’s all I ask.

 

FAVORITES

Author: Hugo Whiskard
Link: Tableau Public

Author: Emily Chen
Link: Tableau Public

Author: Steve Fenn
Link: Tableau Public

Author: Matt Francis
Link: Tableau Public