Big Data: Too big to fail?

Big Data Fail montage
With ongoing hype surrounding (1) the exercise of Big Data mentality, and (2) implementation of Big Data procedures, and (3) application of Big Data software solutions, I really thought I was onto something original and clever here with the too-big-to-fail motif: “Big Data is TOO BIG to Fail!” ha ha ha
I figured it would be easy to write about how businesses are frequently encouraged to just “do” Big Data and–Bam!–they will become overnight successes, outpacing their competitors, $aving million$ of dollar$, and growing their customer bases like crazy. Big Data Magic! Everyone who touches Big Data turns to gold! Capitalize on it now or risk failure!!
However, the reality is that Big Data—just like any business initiative–most assuredly CAN fail if the mentality is not goal-oriented. Or if the procedures are not relevantly planned. Or if the software solutions are insufficiently targeted. Any or all of these factors could easily lead to misguided data interpretation and faulty conclusions. Big Data does not have to end in failure, of course. But, like the old saying goes: “Failure to plan is planning to FAIL.” And what struggling business wouldn’t be ready to blame new, faddish, Big Data efforts for such failure?
Anyway, it turns out the too-big-to-fail motif has already been broached by better minds than mine. Here are a few entries:

About statsoftsa

StatSoft, Inc. was founded in 1984 and is now one of the largest global providers of analytic software worldwide. StatSoft is also the largest manufacturer of enterprise-wide quality control and improvement software systems in the world, and the only company capable of supporting its QC products worldwide, with wholly owned subsidiaries in all major markets (StatSoft has 23 full-service offices, on all continents), and its software is available in more than 10 languages.

Posted on April 8, 2013, in Uncategorized. Bookmark the permalink. Leave a comment.

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