Finding the Little in Big Data

by Angela Guess

Paul Miller of Cloud Ave recently wrote, “Big Data has a problem, and that problem is its name. Dig deep into the big data ecosystem, or spend any time at all talking with its practitioners, and you should quickly start hitting the Vs. Initially Volume, Velocity and Variety, the Vs rapidly bred like rabbits. Now we have a plethora of new V-words, including Value, Veracity, and more. Every new presentation on big data, it seems, feels obligated to add a V to the pile.”

He goes on, “But by latching onto the ‘big’ part of the name, and reinforcing that with the ‘volume’ V, we become distracted and run the risk of rapidly missing the point. The implication from a whole industry is that size matters. Bigger is better. If you don’t collect everything, you’re woefully out of touch. And if you’re not counting in petas, exas, zettas or yottas, how on earth do you live with the shame?”

Miller continues, “From the outset, though, size was only part of the picture. Streams of data from social networks, traffic management systems or stock control processes raise a lot of challenges because of the speed with which data must be ingested, or the rapidity with which actionable decisions must be taken. Data volumes may only be a few gigabytes or – oh, the embarrassment – megabytes, but the challenge is still very real. Combining data of different types from disparate sources also creates opportunities.”

Read more here.

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