Big Data

Big Data as described by IBM VP Paul Zikopoulos

imagesI just finished reading Big Data for Small and Medium Businesses on IBM’s Forward View. In the article, IBM VP Paul Zikopoulos talks about big data and its importance to the small and medium business today.

Paul describes big data thusly:

I want to start out by noting that big data isn’t only about the volume of data, it’s about bringing data together that hasn’t been correlated in the past. Big data can indeed be about more data, but it doesn’t have to be.

Well said. Big data isn’t always about the size of the data, it’s what you do with your data and what questions and answers you find with that data.

There are a few other interesting tidbits in the Forward View article. Paul describes four components of big data. I won’t go into details here (to get you to jump over and read the article yourself), but I will highlight those four components and add my own thoughts around the.

First, the components as described by Paul:

  • Volume of data
  • Variety of data
  • Veracity of data
  • Velocity of data

Impressive break-down of big data. I like these components and I like Paul’s description of them. Each component quite accurately hits the main aspects of big data that an organization needs to think about.

The volume of data is important. As I’ve said before, the data-set itself doesn’t have to be huge, but the organization needs to understand the size of the data to be able to manage it.

The variety of the data is another area that is important but often over-looked by many organizations. Data exists in many forms and can come from many different sources. One of the important things about the big data movement is the ability to a take disparate systems and data sets and combine them to find interesting contextual information for decision making purposes.

The third component is the veracity of the data. If you can’t trust your data, what good is it? To ascertain the veracity of data you’ve got to ask the ‘what, when, how, where, who’ questions of your data sets.

Lastly, the fourth component is the velocity of the data. Velocity covers many areas but is generally concerned with how fast data is growing and being processes. If your data set is growing faster than you can process it and/or understand it, you’ll need to revisit your analytical approaches.

These four components do a great job of breaking big data down into bite-sized chunks for organizations to understand. They also do a great job of helping organizations to understand the main areas that must be managed in order to ‘do’ big data well.

IBMThis post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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About Eric D. Brown, D.Sc.

Eric D. Brown, D.Sc. is a data scientist, technology consultant and entrepreneur with an interest in using data and technology to solve problems. When not building cool things, Eric can be found outside with his camera(s) taking photographs of landscapes, nature and wildlife.
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