In my previous big data post, we discussed the three necessary criteria for information to provide insights that are valuable. Through this discussion, we learned the key to insights discovery.
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Updated 8 months ago
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Hello Stuart,
Thank you for the comment. And your joke definitely captured the creative and nonlinear aspect of Exploratory Data Analysis (EDA).
However, I must re-emphasize that pure creativity is not sufficient, because it may take you too long to find the insights. There are also a lot of rules, techniques, and methodologies to EDA. In fact there are so many that John Tukey himself said that it cannot be catalogued.
"No catalogue of techniques can convey a willingness to look for what can be seen, whether or not anticipated. Yet this is at the heart of exploratory data analysis." -- John Tukey
So EDA should be seen as the creative and nonlinear exploration of data within a vast boundary of tools developed in mathematical and statistical science. And because math and statistics is so general, and its boundary so vast, it rarely pose constraint on the creative aspects of EDA.
Alright, thanks again for the conversation.
And I hope to see you again next time.