Introduction
Here is a famous quote on learning:
We Learn . . .
10% of what we read
20% of what we hear
30% of what we see
50% of what we see and hear
70% of what we discuss
80% of what we experience
95% of what we teach others.
If we create a similar ordering on ability to interpret data in various forms – the order will surely look like this:
Text < Table < Charts < Interactive Charts
On the other hand, the amount of data which needs processing and interpretation is increasing by the second. Combined, these two factors are making data visualization an integral form of data science workflow – probably more important than ever before.
In order to address this need for creating simple, yet powerful visualization, there are multiple tools which can come in handy. However, a lot of analysts & data scientists are not aware of these tools. Hence, we have created an infographic, which provides high level overview of various tools people use for creating data visualization.
What do you think about the infographic? Do you think, there are other tools which should be part of this infographic? If yes, let us know through comments below
P.S. Online Data Hackathon 3.x coming up on 5th & 6th September. Register now
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Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.
