Every industry loves a buzzword. A catchy phrase to throw into PowerPoint and get the buying masses drooling at the art of the possible. The world of IT and data is notoriously wonderful in this regard. Who amongst us can honestly say they haven’t oohhed or indeed aahhed at a speed of thought or bleeding edge technology soundbite?

But as the glossy brochures start to fade and project deadlines whoosh past, we come to realise that Big Data is just…data and that the only thing bleeding edge is a nasty papercut from a change request form.

The concept of data literacy is garnering much attention at present. A transient, ultimately meaningless addition to the slogan graveyard…?

Qlik defines data literacy as:

The ability to read, work with, analyse and argue with data

I like this definition, and not just because it has the word argue in it. I like it because it’s not technical. I like it because it made me realise that data literacy is, in truth, a life skill.

Data is everywhere. 90% of the data in the world was created in the last two years and the pace of growth is only going to quicken. If we cannot read it, work with it, analyse it and challenge it then how can we make sense of the world?

Source: Eye Witness News (https://ewn.co.za/2019/02/20/infographic-budget2019-budget-expenditure-breakdown)

This gem recently appeared on a local news website and gives a breakdown of the latest ANC budget by area of spend. Let’s look at this visual masterpiece in the context of the data literacy definition.

I can read it and can do some very basic analysis and comparisons in my head. It would be a lot easier to do so if the data slices were sorted by size, and easier still in a descending bar chart. There’s very little data to work with. Immediately I want to know things like:

  • What are the numbers behind the headline number?
  • Have things changed since last year and if so by how much?
  • What was spent in relation to last year’s budget and is it have significance?

As for arguing

I’ve already ranted about pie charts here so there’s no need to go over old ground except to mention that the colours are awful, the ordering is non-existent and that a pie chart is entirely the wrong way to represent this data.

Oh, and I’d argue that the percentages on the pie slices need to add up to 100%.

When I noticed the numbers didn’t add up, I initially gave it the benefit of the doubt and assumed a rounding error was to blame.

Not so.

The actual percentage for learning and culture for example is 21.66% and yet it mysteriously appears as 24% on the pie chart. The cost of servicing debt is 11.34% but is rounded down to 10%.

Ladies and gentlemen, may I present the Covfefe Chart. It’s meaningless and essentially made up.

In this case I think it’s just a bad chart – but what if the discrepancy had some sort of motivation? What if a government was trying to downplay a debt figure and over-inflate an education figure a few months out from an election…?

Consider the visual below:

The numbers are identical to those used for the pie chart but, by exploiting a visual trick in comparing the largest and smallest items via a radial chart, I’m able to lend weight to a different argument.

Andy Cotgreave produced perhaps the best and most simple example of why you have to argue with data before you trust it:

Source: http://gravyanecdote.com/uncategorized/should-you-trust-a-data-visualisation/

All visuals are based on the exact same set of data. In fact, the only differences between them are the orientation of the graph, the title and the colour.

According to a Gartner survey of Chief Data Officers, poor data literacy is the second biggest roadblock to progress with data and analytics – a data and analytics project market that’s worth an estimated $200bn in 2020.

As the leader of the free world and honorary patron of the Covfefe Chart might say – that’s Yuge.

At Synergy we have a team of people dedicated to helping people become more data literate through best practice, training and advice. So if you want to climb out of your trough of disillusionment and scale the plateau of productivity* then why not talk to us?

*buzzwords not included.

Connect with us!

Post written by Nik Eveleigh, Principal BI Consultant, Synergy.

Other articles in this series:

Making Healthy Data Choices – published September 2018  
A helping hand(le) for your data – published October 2018  
All roads (eventually) lead to data – published November 2018  
The 12 Vizzies of Christmas – published December 2018  
Don’t sweat the small stuff – published January 2019  
The Devil is (sometimes) in the Detail – published February 2019

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