Some thoughts on big data challenges

Here is a list of challenges from my personal encounters with the subject:

1. How to make use of unsupervised data? 
2. Untangling mixed phenomena
3. The need for on time (unexpected) decisions
4. Identifying "black swans"
5. Deploying legacy data - this is similar to #1 using unsupervised data
6. Devising a method for exponential growth of data 
7. Using old tools in a new environment
8. Is there any size that is too big to handle?
9. Statistics in a dynamic reality
10. What would be considered a right hypothesis?
    (or is there such a thing as a wrong question to ask?)

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A Buddhist story about blind men trying to describe an elephant:

Five blind people were asked to describe an elephant. Each felt a part of the elephant. One person felt the elephant's trunk and said it is just like a plow pole. A second person touched the elephant's foot and said it is just like a post. A third person felt the elephant's tusk and said it is just like a plowshare. A fourth person had a hold of the elephant's tail and said it is just like a broom.  A fifth person felt the elephant's ear and said it is like a winnowing basket. As each one described the elephant, the others disagreed...

http://www.yoism.org/?q=node/221