Data Visualisation

What is Data Visualization?

Data visualization is a graphical or pictorial representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

“A picture is worth a thousand words.”

Nowadays, in the era of big data, when businesses are inundated with information from varied data types and from on-premises and cloud-based sources, that old saying has never been more relevant.

Visuals make analysis much easier and faster and offer the ability to see briefly what matters and most people respond far better to visuals than text – 90% of the information sent to the brain is visual, and the brain processes visuals at 60,000 times the speed of text.

Here is a video explaining what data visualization in 3 minutes!

Why do we use Data Visualization?

Drawing conclusions from massive data sets, or even extracting useful knowledge from them, is virtually impossible without data visualizations. Data Analysts break down this data and present it with data visualization methods for the decision-makers in organizations to understand.

Designers can make knowledge understandable for stakeholders by using data visualization techniques.

Common general types of data visualization:

There are myriad different types of charts, graphs and other visualization techniques that can help analysts represent and relay important data.

  • Charts
  • Tables
  • Graphs
  • Maps
  • Infographics
  • Dashboards

More specific examples of methods to visualize data:

  • Area Chart
  • Bar Chart
  • Box-and-whisker Plots
  • Bubble Cloud
  • Bullet Graph
  • Cartogram
  • Circle View
  • Dot Distribution Map
  • Gantt Chart
  • Heat Map
  • Highlight Table
  • Histogram
  • Matrix
  • Network
  • Polar Area
  • Radial Tree
  • Scatter Plot (2D or 3D)
  • Streamgraph
  • Text Tables
  • Timeline
  • Treemap
  • Wedge Stack Graph
  • Word Cloud
  • And any mix-and-match combination in a dashboard!


What are the best data visualization tools?

  • Grafana,
  • Chartist.js,
  • FusionCharts,
  • Datawrapper,
  • Infogram,
  • ChartBlocks,
  • D3.js.

The best tools offer a variety of visualization styles, are easy to use, and can handle large data sets.

The 10 best data visualization blogs to follow:

1. Storytelling with Data by Cole Nussbaumer Knaflic 

2. Information is Beautiful by David McCandless 

3. Flowing Data by Nathan Yau 

4. Visualising Data by Andy Kirk 

5. Junk Charts by Kaiser Fung 

6. The Pudding by Matt Daniels 

7. The Atlas by Quartz Media 

8. Graphic Detail by The Economist

9. US Census and FEMA by The US Census Bureau; The US Department of Homeland Security 

10. Tableau Blog by Tableau

If you are interested in getting more information, check these 12 great books about data Visualization:

1. “Information Dashboard Design: Displaying Data for At-a-glance Monitoring” by Stephen Few

2. “Beautiful Visualization, Looking at Data Through the Eyes of Experts by Julie Steele, Noah Iliinsky”

3. “The Accidental Analyst: Show Your Data Who’s Boss” by Eileen and Stephen McDaniel

4. “The Functional Art” by Alberto Cairo

5. “The Visual Display of Quantitative Information” by Edward R.Tufte

6. “Cartographies of Time: A History of the Timeline” by Daniel Rosenberg, Anthony Grafton

7. “Information Graphics” by Sandra Rendgen, Julius Wiedemann

8. “Visual Thinking for Design” by Colin Ware

9. “Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic

10. “Knowledge is Beautiful” by David McCandless

11. “Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics” by Nathan Yau

12. “The Big Book of Dashboards” by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave


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