Who Cares if a Toilet Maker Has More Data Than the Library of Congress? [Infographic]
The Library of Congress is so often used to compare how much more data we produce than could ever be stored in a building with seemingly endless shelves filled with books.
It’s an analogy that is used to show much data we now create. But, really, who cares if a toilet maker has more data than one of the world’s largest libraries? Data is meaningless if it has no context. The books in the Library of Congress have far more value than the stagnant ponds of data that gets collected in the making of a porcelain throne.
McKinsey Quarterly published a chart today that gives a picture of how much data is getting produced by the 17 sectors of the U.S. market. The chart shows big data, its scope and the need to make it more meaningful.
McKinsey found that companies with about 1,000 employees have on average more information than the Library of Congress. Well, okay, but, really is that the point?
What if we tore out the pages of each of the books in the Library of Congress, put them in a giant pile, then blew a giant fan over the mounds to mix it all up? It would be impossible to learn much of anything with the “data,” in that form, Instead, the bound books have deep connections to millions of people who have learned from reading and applying the information to their lives.
Apply this concept to big data and it’s apparent who the winners are. They are the companies that use big data and business analytics to guide their decisions. As McKinsey points out these companies are also more productive and have higher returns on equity than competitors that do not.
Services Angle
Jeff Kelly of Wikibon has published an excellent study of the big data market. We talked today in our weekly editorial call about the report. I was curious about the role of service providers.
“We are still in an education phase,” Kelly said.
People still want to know what is Hadoop? What is big data?
The conversation needs to turn. We need to get beyond the shallow views about the amount of data we have. Learning how to use it makes far more sense.
Here’s a good example, courtesy of McKinsey: “Are you ready for the era of ‘big data’?”
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