Accessible Power BI Data Storytelling
We've created a report that uses open data published by the World Bank to explore global trends in wealth & health. This report has been published to the Power BI community data stories gallery.
The video below walks through the report. It is an example of how technology, data and visual design can be combined to engage people and turn data into actionable insights.
The report captures many of the techniques we use when we develop analytics for our clients. We find that design concepts such as branding, accessibility and persona driven user journeys are key to enabling the report to have the impact intended.
You can find the report on the Power BI Community Data Storytelling Gallery.
You can also watch a discussion about brand, design, usability and accessibility of the report: Accessible Data Storytelling with Power BI: Design Concepts and Accessible Colours
Hello and welcome to this Tour of endjin's, World Health and Wealth Report. The report uses open data that's been provided by the World Bank, and we are looking specifically at wealth data in the form of GDP (gross domestic product) per capita, and health data where we're using life expectancy as a metric, across all of the countries in the world.
We've got data for 217 countries and you can see those represented here on a map. Each country is represented by a point on the map and the color coding shows which of the seven regions, which the World Bank uses to organize country data, those countries belong to.
If we look at a country like Australia in a bit more detail we can see that their health as a nation over the last 60 years has increased from around 70 to 83 years for the life expectancy. The wealth has increased significantly over the same period. They're now generating around 60,000 US dollars per head of capital in terms of gross domestic product, and their population has grown steadily over that time as well.
So what would be interesting to explore is do we see those kind of trends happening globally? Are all countries getting healthier and wealthier, and are they all growing as Australia is? Let's dig into that data now.
So first off, if you look at health we're exploring the average median health by region over the last 60 years by decade. And you can see an encouraging upward trend. And that's born out by the metrics that we see in the central chart. So if we focus on the median across all countries, you can see that's been increasing steadily over that time period. Also in the final chart, if we look at the gap there's two metrics here. The gap between the max and the min in terms of the most healthy country and the least healthy country, and also the upper versus lower quartile figure as well.
You can see that despite this upward trend in the 1970s, generally the gap between the healthiest nations and least healthiest nations has been reducing over time, which is great to see.
If we now pop back and explore wealth. This is annual data, so it's a more detailed view of the data. Wealth data does tend to be a bit more volatile because you get those big economic shocks like the the financial crisis back in 2008. But if we look at the distribution data again here the median, which is the solid black line, has been steadily increasing when you look across all countries. So that's great. Generally the world is getting a wealthier place. But what's worrying is the wealth gap. Now this is a logarithmic scale, so note that first of all. You can see here that by both measures, max versus min and upper quartile versus lower quartile, see that gap has only increased over time.
So back in 1960, the max versus min was 3,000 US dollars. Today it's around 173,000 US dollars. So it's increased by two orders of magnitude. So that feels like a trend that's going in the wrong direction.
If you look at population now here we're representing every country in the world on a tree map. So the larger the country by population, the bigger the area it takes up on the tree map. You can see from the top right hand corner here that population by region has been growing. Generally quite steadily.
Although sub-Saharan Africa, which is this orange line, seems to have accelerated in its growth compared to some other regions where, even visually here on the chart, you can see that the population is growing at a slower rate.
We know for countries like Japan, if we zoom into Japan, that in the last 10 years fertility rates in Japan have have been negative. There's a slight decline in the population in Japan as a result of that.
We can also see things like if we zoom into Europe for example, and we look at Ukraine it's seen significant decline in population, but that's more driven by economic migration rather than fertility rates.
So finally, if we put all this data together we can plot it on a single chart and this was inspired by Hans Rosling. He's got a video on YouTube, which is well worth the watch. It's called 200 countries, 200 years in four minutes, and it's very much worth the watch. We've applied his technique to plotting all of the countries of the world on a single chart. We've only got 60 years of data, but as you'll see in a second, we can achieve a similar result.
So the way this works is every country is plotted on the chart. Life expectancy drives their position on the X axis, so that's the measure of their health. So the healthiest countries are towards the right.
Then wealth is measured on the Y axis using GDP per capita. So the richest countries are towards the top of the charts. So you've got the rich and healthy countries and the poor and unhealthy countries separated on the chart.
So if you wind the clock back to 1960 and play the data year by year, you can see how the countries are generally moving towards the right and also upwards on the chart.
But you can also see times where countries like Cambodia take massive shocks. So in the late 1970s Cambodia suffered from famine and war, and that had a massive impact on their life expectancy. Similarly, you can see Rwanda here, we've just seen Azerbaijan, and Iraq have a huge shock through the 1990s in terms of wealth. But generally we can see that positive trend of all of the countries moving in that positive direction towards the top right hand corner of the chart.
But it's also quite interesting once we get to the end of this journey, we can also filter countries that the World Bank would consider to be low income countries. And we can also show countries that the World Bank would consider to be high income countries. And there you can see very starkly the gap that exists between those countries in terms of wealth, but also along the X-axis in terms of health. So this brings it home quite starkly that whilst globally health and wealth have been going in the right direction, we've still got a long way to go before we have genuine parity and consistency around the world in terms of those two metrics.
I hope that's been useful and a nice demonstration of how to tell data stories using Power BI and how strong visual design can help bring that data to life. And if you've got any questions or any thoughts or any feedback, we'd love to hear from you.
Thanks for watching.