The way we view and consume data has changed so much in the last few years. For decades we have been using charts to help us understand business data but we now have much more data to analyse and those same old charts are just not cutting it. Everything is changing and you need good Data Visualisation to get real insight from your companies data.
We can now interact with our charts, work directly with the data and navigate through our information like never before. Being able to interact quickly with our data is what leads to insight. To experience the benefits of data visualisation, you must avoid the pitfalls.
#1 Colour Abuse: Too much colour is bad
Colour plays an important role in data visualisation. It’s an opportunity to further your companies branding but don’t overdo it in data visualisation so choose your colours carefully.
- Analysis comes first. Despite what your branding department says, your brand colours may not be the best choice for data visualisations.
- The wrong colour can lead to confusion or even worse, misinterpretation.
- Consider the colour blind. Did you know that 8% of men are colour blind? Try to use shapes and colours that are easy for everyone to see.
- Don’t rely on colour alone to convey meaning.
#2 Misuse of Pie Charts: Not all pies are tasty
We all love a good pie chart, but there is nothing less satisfying than a tiny sliver. By trying to squeeze too much information into a pie chart, the big picture can be lost. Too much detail leaves the viewer unsatisfied and confused.
Try to avoid using pie charts side-by-side as it can loo messy and it’s an awkward way to compare data.
- Pie charts work best for limited data sets that let you easily distinguish each slice of the pie.
- Use pie charts to compare parts of a whole. Don’t use them to compare different data sets.
- Order slices from largest to smallest for easier comparison.
#3 Visual Clutter: Keep it simple
Making discoveries in a cluttered visualisation is like finding a needle in a haystack. Too much information is the enemy of clarity. Any ‘chart junk’ will crowd a visualisation obscuring meaning and can lead to inaccurate conclusions.
- Limit the number of KPI’s in a dashboard to 9 or less. Too many indicators are distracting.
- Keep the visualisations simple. The less there is to interpret, the easier it is to understand.
- Play with different formats until you find the simplest and cleanest format. Minimalism wins over cluttered when it comes to data visualisation.
#4 Poor Design: Beauty does not mean effective
Just because a dashboard looks beautiful it doesn’t mean that it’s effective. Effective visualisations incorporate design best practices to enhance the communication of data.
- Get professional designers to design your dashboard, they know what they’re doing.
- Don’t just create visuals and dashboards; design them.
- Work with your designers to ensure that the visualisation is as effective as it can be.
“DESIGN IS NOT JUST WHAT IT LOOKS AND FEELS LIKE. DESIGN IS HOW IT WORKS.”
– STEVE JOBS
#5 Bad Data: Pretty doesn’t cut it if the data is wrong
Great visualisation starts with great data. If your visualisation reveals unexpected results, you may be the victim of bad data.
- Identify and correct data issues early.
- Use your charts to spit issues with your data.
- Address any data issues before present your data. Don’t let your visualisation take the blame for bad information.
- Understand the difference between an unexpected discovery and a data issue.
Origionally published by Qlik
Now that you’re ready to start planning your data visualisation, get in touch with Satsumas to discuss your data discovery needs.
We are focused on solving business problems where complex data is involved. We deliver business intelligence solutions using intuitive visualisations to support data driven decisions through data discovery and self-service analytics.
Satsumas have worked with financial, pharmaceutical, utility, retail and mining companies and understand the challenges you need to overcome.