The boss’s boss looks out across the server farm and sees data—petabytes and petabytes of data.

That leads to one conclusion: There must be a signal in that noise.

There must be intelligent life in that numerical world—a strategy to monetize all those hard disks filling up with numbers.That job falls on your desk, and you must now find a way to poke around the digital rat’s nest and find a gem to hand the boss.[ Download the InfoWorld megaguide: The best Python frameworks and IDEs. | Learn to crunch big data with R. | Keep up with hot topics in programming with InfoWorld’s App Dev Report newsletter. ]
How? If you’re a developer, there are two major contenders: R and Python.

There are plenty of other solutions that help crunch data, and they live under rubrics like business intelligence or data visualization, but they are often full-service solutions.
If they do what you want, you should choose them.

But if you want something different, well, writing your own code is the only solution.

Full-service tools do a good job when the data is cleaned, buffed, and ready, but they tend to hiccup and even throw up when everything is not quite perfect.To read this article in full or to leave a comment, please click here

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