Is That the Sound of a Bubble Bursting?


Hold tight. The big-data bubble is about to burst. And you may recall reading it here a few weeks ago: Editor in Chief Beth Schultz raised the issue in Big-Data Meltdown & 7 Other 2013 Predictions.

But plenty of others are also looking into similarly bleak crystal balls, at least as far as the fate of big-data is concerned.

In a New York Times post that questioned "the limits and shortcomings" of big-data technology, reporter Steve Lohr suggested that intuition is at least as valid as math modeling, predictive algorithms, and artificial intelligence:

In so many Big Data applications, a math model attaches a crisp number to human behavior, interests and preferences. Claudia Perlich, chief scientist at Media6Degrees, an online ad-targeting start-up in New York, puts the problem this way: "You can fool yourself with data like you canít with anything else. I fear a big-data bubble."

Perlich is worried too many people will start rushing to become "data scientists," do poor work, and give big-data a bad name.

Bill Franks, chief analytics officer for Teradataís global alliance programs, was even more emphatic in an International Institute for Analytics blog:

I predict that in 2013, the big data bubble will begin to spring some serious leaks. The bubble may not fully burst in the next 12 months, but it will begin to deflate...

While big data can (and will!) drive major change in the coming years, the fact is that every type of big data wonít drive change for every organization. Each organization will have to find its own path to success given its own unique business model and relevant big data sources.

Actually, people have been predicting the demise of big-data for a while now. More than a year ago, Eric Knorr, editor in chief at InfoWorld, wrote, "First there was the dot-com bubble; then the housing bubble. But nothing will compare to the big data bubble."

So what are some of the issues? Bruno Aziza, vice president of marketing at big data analytics company SiSense, argues that big-data is too expensive -- and not necessarily big. In a post titled "Why I donít buy the hype about 'big data'," he suggested that big-data needs to be refined and redefined. "We need to approach big data differently, and design solutions that allow smaller companies [to] take advantage of this opportunity," he wrote.

Part of the problem with big-data is that it is not necessarily big -- and badly needs a better definition, Aziza argued:

What if, instead of focusing of the proverbial 3 Vís (velocity, volume and variety), we tried something like this: "Big data is a subjective state that describes the situation a company finds itself in when its infrastructure canít keep pace with its data needs."

What do you think? Is big-data headed for a fall -- or is it just going through a natural state of evolution?

Noreen Seebacher,

Noreen Seebacher, the Community Editor of Investor Uprising, has been a business journalist for more than 20 years. A New York City based writer and editor, she has worked for numerous print and online publications. Her work has appeared in The New York Times, the New York Post, New York’s Daily News, The Detroit News, and the Pittsburgh Press. She co-edited five newsletters for Real Estate Media’s GlobeSt.com and served as the site's technology editor.

She also championed the commercial real estate beat at The Journal News, a Gannett publication in suburban New York City, and co-founded a Website focused on personal finance. Through her own company, Stasa Media, Noreen has produced reports, whitepapers, and internal publications for a number of Fortune 500 clients. When she's not writing, editing, or Web surfing, she relaxes in an 1875 Victorian with her husband and their five kids, four formerly homeless cats, and a dog.

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Re: CNN's take
  • 1/11/2013 12:14:55 PM
NO RATINGS

I'd agree -- too much at stake in the start-up business to risk it all on intuition. Got to back it up with data!

Re: CNN's take
  • 1/11/2013 9:42:01 AM
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I'm not so sure "intuition" is a better way to price than using data necessarily. It all depends on what the data is and how it's interpreted. If the forumula used isn't valid then intuition may as well be the choice used. But, if the data collected indicates real correlation with buyer behavior then go at it. But, bubble do burst at some point, so we'd better be ready!

Re: The Problem With Big Data
  • 1/8/2013 7:25:07 AM
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@Noreen, the video spells this all out nicely and I like the comparison to the internet bubble.  The internet is still around and it has not only changed many business processes it has changed our day to day lives.  I don't think the average citizen is going to be doing analytical work with big data but I do think that it is going to change many business processes the same way the internet has.

Re: CNN's take
  • 1/7/2013 2:41:28 PM
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Ariella, no surprise there, though, would you say? Yes, we're early days in big-data and in developing the talent needed to really exploit its availability. Should be an interesting few years....

Re: CNN's take
  • 1/7/2013 12:06:05 PM
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@Beth Yesterday's Gigaom article argued along the lines of we've got a long way to go in big data.

"data scientists are the designers and the content creators of today, not the software engineers or the IT bottleneck.

Every organization will need someone wearing the data scientist hat just like very organization has people responsible for product, sales, marketing and support. Unfortunately, to date, the tools available to data scientists have been rudimentary. Data scientists have had to learn diverse and complex computer languages for working with data. That world is changing as we create simpler ways for data scientists to use big data.

Re: The Problem With Big Data
  • 1/7/2013 10:24:06 AM
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Re: The Problem With Big Data
  • 1/7/2013 8:30:44 AM

@Hyoun Park, excellent insight.  The fact that anyone can collect data and make observations doesn't make it a valuable big data implementation.  Knowing the relationship between your data and real life results is often a missing component and it results in a lot of guessing.  I don't think there is a bubble bursting yet, but if there is one that bursts I think it will be the one size fits all bubble that goes first.  Analytical business practices  aren't going away, and big data is a very important tool there when it is used correctly.

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