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Big Data

Searching for causation

If you are an author, there are three things you worry about.

  1. How many have purchased the book?
  2. How many have read the book?
  3. How many have understood the book?

If you have written the book with the aim of making money, then asking the first question is sufficient. If you believe that you have written a masterpiece and that it is important to you that as many should read it, then the second question is sufficient and you should not be worried about the first. Book piracy is the last thing you have in mind if you are interested in the second question. The third question is obviously meant for those practicing Zen and the mystic.

The first question can be answered by Big Data. Amazon, Flipkart or anybody who have access of all purchases can easily answer the same after a deep dive in the retail data. To make it worth your while they can also tell you what else was bought along with it and what discount were given etc. This is easy because you are worried about ‘how many books’.

The second question is more difficult. You must search for a surrogate or make it a point of questioning every single buyer the question ‘have you read the book?’. For all you know they may have bought it as a gift for an unwilling or an uninterested nephew or a niece perhaps.

The Big Data oracle will also tell how many have rated the book and hopefully you can then use the intelligence within to come to an understanding of how many have read the book.

The third question of how many have understood the book, and if they haven’t understood, why had they not is out the realm of Big Data.

You see Big Data does not help in understanding causality. Causality is the realm of the business and the philosopher. While jumping to conclusions is the forte of us human beings, arriving at a proper cause for any correlation good or bad is also the forte of the same human being!

If the answer to question three is ‘very less’ and then you ask the question two and then question one and then you seek an answer – only 10 books have been sold, then you had your hypotheses and you have verified the same.

However if the answer to question one is say 20 million, the answer to question two may be 1 million and the answer to question three may still be 10! Perhaps like JK Rowling, Agatha Christie or Erle Stanley Gardner you should be interested in the outcome of only question one.

Are you still searching for the why?




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