Big Data Superficialities
October 2, 2016
When one needs to understand Big Data, what’s the go to resource? A listicle of Big Data generalities. Navigate to “6 Illusions Execs Have About Big Data.” The article points out that Big Data is a buzzword. Shocker. And the chimera identified? Here you go:
- All data is Big Data. Yep, a categorical affirmative. Love those “all’s”.
- Big Data solves every problem. Another categorical affirmatives. Whether it is the Zucks’s curing “all” disease or Big Data dealing with “every” problem, the generalization is rock solid silliness.
- Big Data is meaningless. The statement leads to this parental observation: “To make big data less meaningless, you need to be able to process and use it.” I am curious about the cost, method, and accuracy of the outputs in the real world.
- Big Data is easy. The enumeration of the attributes of a pair of women’s shoes resonates with me. I like flats.
- Imperfect Big Data is useless. Nope, Imperfect.Many data sets have imperfections. The hard work is normalizing and cleaning the information.
- Only big companies need big data. I like the balanced sentence structure and repetition. The reality, however, is that small outfits often struggle with little data. A data set can easily overwhelm the small outfit’s resources and act like a stuck parking brake when closing deals and generating revenue are Jobs 1 and 2.
Amazing stuff. When I encounter information similar to that contained in the source document, I understand how many vendors close deals, pocket dough, and leave the lucky buyers wondering what happened to their payoff from Big Data.
Stephen E Arnold, October 2, 2016
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