Data Visualization

Data visualization or data visualization is viewed by many disciplines as a modern equivalent of visual communication. It is not owned by any one field, but rather finds interpretation across many (e.g. it is viewed as a modern branch of descriptive statistics by some, but also as a grounded theory development tool by others). It involves the creation and study of the visual representation of data, meaning “information that has been abstracted in some schematic form, including attributes or variables for the units of information”

There are many different data visualization tool in the market. I am personally fond of Tableau as it has really cool features. Most business intelligence software vendors embed data visualization tools in to their products, either developing the visualization technology themselves or sourcing it from companies that specialize in visualization.

[Ref: https://en.wikipedia.org/wiki/Data_visualization]

I liked the list of popular data visualization tools that KDnuggets compiled:

  1. Tableau
  2. Canva
  3. D3.js
  4. Datawrapper
  5. Dipity
  6. Dygraphs
  7. MS-Excel
  8. Fusion Charts
  9. Gliffy
  10. Google Charts
  11. HighCharts
  12. iCharts
  13. InstantAtlas
  14. Leaflet
  15. PiktoCharts
  16. Timeline.js
  17. Polymaps
  18. Visual.ly
  19. WolframAlpha
  20. ZingChart

In my future posts, I will keep adding details on above tools. Please feel free to add here if you are aware of any other popular visualization tools and pros and cons of the above listed tools.

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