First of all, I have to disappoint you, there is no such thing as the perfect dashboard. With that out of the way, let me help you create a well-designed dashboard then.
There are many types of dashboards based on role, type of displayed data, data area, data span, or even interactivity, but all of them have to follow these 10 rules.
Dashboards often need to present a large amount of information in a limited amount of space. The design should be intuitive and allow easy comparison — everything needs to be visible at a glance and properly allocated.
A few days ago I came across one of the GfK reports on FMCG e-commerce and the charts dedicated to e-commerce buyers got my attention. At first glance, it looked okay —quite minimalistic with good visual hierarchy but the longer I look at it, the odder it seems. First of all, the chart is unnecessarily complicated, the usage of both stacked bar chart and grouped bar chart brings nothing but confusion.
This week I decided to makeover a commonly overused chart in a market research field — a stacked column chart for time series. It took me a couple of years and a lot of bad chart choices to come up with the conclusion that the line chart is probably the best and the simplest way of presenting a time series.
The chart I picked up is from one of the latest Kantar reports and it shows a change in GB spend on six categories over the course of 2 years. The main purpose of the chart is to show the…
This week I came across Eurostat’s Instagram account, which is a resourceful place when you are looking for European statistics. The one visualization particularly caught my eye because of the usage of quite an uncommon chart — a combined chart consisted of a column chart and some variation of a dot plot. The chart itself is about changes in the employment rate in the EU during the pandemic and it shows three different levels of data — a total change for each of the countries, change for each gender within the country, and an aggregated data for the EU.
This week I’ll cover the advantages of grouping multiple line charts into few slopegraphs. I picked up the visualization by PEW Research Center that covers the perception of criteria for national belonging among 4 countries.
The visualization presents the change that happened among these countries over the course of four years. It consists of a matrix of 16 different line charts that focus on the change of one criterion in one country. Because everything is kept separate you read this chart almost like a table — you process the numbers instead of taking advantage of visual representation. …
A few days ago PEW Research Center published an article on fertility in the U.S. before the pandemic. One of its takeaways was the decrease in the education gap in fertility over the past two decades. This was supported by the slopegraph showing the share of women who have ever given birth across different levels of education.
I think that the chart selection and limiting the data points was an excellent choice. So what’s wrong with this data visualization?
Last week I came across some unusual dot plot that was done by The Economist. At first, I thought that this is a refreshing way of using this chart. But the longer I look at it the stranger it seemed. The chart presents the feelings about removal of US troops from Afghanistan. It was created to allow the comparison of three “Yes/No” questions among three different groups — all Americans, republicans, and democrats.
This time I’ll focus on another way of presenting the Likert scale. The original chart by PEW Research Center inspired me to explore the diverging chart, which, in my opinion, is a better way of showing polarization in opinion. The chart shows the change in feeling about Trump over the course of his presidency among three groups — all Americans, republicans, and democrats.
This is the third post of the series about incremental improvements that can be done in order to make a visual design better. In each post, I analyze the data visualization to see what works, what doesn’t, and what to do to improve it.
In previous posts, I covered small multiples chart and bar chart usage. This time I’ll focus on stacked chart alternative and makeover the chart regarding the EU tourism published on the European Commission webpage.
This is the second post of the series about incremental improvements that can be done in order to make a visual design better. In each post, I analyze the data visualization to see what works, what doesn’t, and what to do to improve it.
In the first post, I covered the small multiples chart done by The Economist. This time I’ll focus on the chart I found in one of the reports a long time ago.
Data Visualization Designer | Tableau Associate | Sociologist with passion for aesthetics