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Virtually Speaking

Dan Kusnetzky, Paula Rooney and Ken Hess

Another take on "Big Data"

By | December 30, 2011, 3:15am PST

Summary: The topic “Big Data” always brings in many reader comments. Here’s a segment of on response that gets to the heart of Big Data use cases.

Every time I post something on “Big Data,” I get quite a bit of Email with readers’ thoughts on a good definition. A reader calling himself /herself “Mikey” sent a very short response that went to the heart of the topic. Here’s a segment of what “Mikey” had to say:”

Think three Vs.

  • Volume - The sheer amount of data, whether from a webscale user base (Twitter, Facebook) or a huge amount of machine/sensor data (clickstreams, power grid monitors etc.)
  • Variety - Data is more than validated strings in fields - it’s text, images, video, and all sorts of machine data formats
  • Velocity - Wherever and whoever it’s coming from, you have to capture tens or hundreds of thousands of writes per second, maybe even millions. You need distributed systems, usually, because if you just try to throw performance and hardware at it you’ll eventually always lose.

I would also add extreme amount of retail point of sale data to the reader’s “Volume” list. Other than that, “Mikey” has the use case nailed.

The technology that supports Big Data, on the other hand, is much to complex to describe in a few short bullets.

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Daniel Kusnetzky is a distinguished analyst and the founder of the Kusnetzky Group LLC.

Disclosure

Dan Kusnetzky

The Kusnetzky Group LLC is an independent technology industry research firm that focuses on system software, virtualization and cloud computing technology.

Dan's opinions are based upon research, personal experiences and actual use of technology. They are not based upon the relationships the company may or may not have with suppliers, end user organizations, the media, consultants or other analysts.

Dan's research is available on a subscription basis through the Kusnetzky Group LLC. Dan's attendance at industry events or at client meetings may be sponsored by the client. Clients may provide hardware or software for testing prior to the publication of analysis that includes that product. Clients may also provide shirts, jackets, coffee cups, folders, backpacks, pens and other event chotchkies. While nice, these don't effect Dan's opinions or insight about those clients or their products.

Biography

Dan Kusnetzky

Daniel Kusnetzky, Analyst and Founder of Kusnetzky Group LLC, is responsible for research, publications, and operations. Mr. Kusnetzky has been involved with information technology since the late 1970s. Mr. Kusnetzky has been responsible for research operations at the 451 Group; corporate and marketing strategy for Open-Xchange; system software and virtualization research at IDC; and program and product management at Digital Equipment Corporation.; Today, Mr. Kusnetzky focuses on system software, virtualization technology and cloud computing.

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RE: Another take on
daviddaly 1st Jan
@CobraA1 nice points.
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RE: Another take on
ssmusoke@... 30th Dec
Excellent, simple precise to the point
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Does my data look big in this?
jorwell Updated - 30th Dec
Of course it may be that your data really isn't that big.

But you got distracted by the misguided notion that denormalization improves performance.

Therefore your correct and correctly sized data has expanded into big data, regularly delivering contradictory results from your duplicated data.

Existing DBMSs are already far too redundant. The future is smaller data not bigger.
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RE: Another take on
CobraA1 30th Dec
"I would also add extreme amount of retail point of sale data to the reader???s 'Volume' list."

You're talking about small text transactions vs . . . oh, I dunno, YouTube videos? A single video is probably as much data as many thousands of POS transactions.

And do you really need every piece of data from every transaction outside of the individual store? For higher level stuff, shouldn't you just be concerned with processed, aggregated data?
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RE: Another take on
daviddaly 1st Jan
@CobraA1 nice points.

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