Big Data Is the New Cloud Computing

Big data used to have a specific meaning. Meant to describe cast-offs such as log files, this information was "big" because of the amount of electronic refuse created when processing, say, an e-commerce transaction. Big data used to be an exercise in digital dumpster diving.

Those days are gone. At the annual South by Southwest Interactive conference, "big data" became a proxy for social data compiled by the likes of Facebook and Twitter. A synonym for capturing sentiment, but on a grand scale. Every company had to become a "big data" company, panelists enthused.

Is that really the case? Or is it just hyperbole? In this interview with The Motley Fool's Alison Southwick, Tim Beyers of Motley Fool Rule Breakers and Motley Fool Supernova says the hype is reminiscent of when "cloud computing" took on generic meaning, and launched early pioneers to new levels of profitability. Please watch, and then leave a comment to let us know what you think.

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  • Report this Comment On March 16, 2013, at 11:46 AM, kennyli89 wrote:

    The pure big data push is beautiful in that we are taking truckloads of data that was once thought to be useless and analyzing it with the availability of super-computing and open source software to come out with astounding information. What once took weeks and months to produce now takes hours and days.

    Recently, I read about a Twitter project to identify psychopaths based on Tweets, which is quite a trivial big-data-analysis matter compared to all the other wealth of information people are digging for, but it represents a public and fascinating step toward the capabilities of big data crunching. Literally, we have become "data miners" to a new degree.

    Unfortunately, true big data and cloud are two individuals to hold hands and stroll down a yellow brick road to dreams coming true. The hardware demands of an effective big data machine are hardly found on public cloud infrastructure, including massive disk I/O and huge bandwidth on the internal network. And the slightest idea of sharing these already-scarce resources with multiple users on the same physical infrastructure should be a nightmare for most big data crunchers.

    That being said, we also see many new public clouds emerging with the capabilities that rival fairly powerful dedicated servers, and I can understand in the demand for big data as a catalyst for this rapid development:

    SSDs are replacing HDDs to maximize disk I/O and make sure that old data travels off the disk and new data travels on the disk as quickly as possible.

    1Gbit networks are becoming dual 40Gbit networks (totaling 80Gbit bandwidth) to make sure the data can get from the storage area to the "brain" (CPU) as quickly as possible and back.

    Virtualized users are throttled in CPU access to ensure a guaranteed, allocated computing power to crunch and analyze all that data to make sure the calculations can be solved in the quickest manner possible, creating new data and cycling the process over and over again to get the information we're looking for.

    Overall, this is a beautiful, organic process that should not be taken for granted, and becomes much more easily appreciated when we take a step back and view the timeline of human computing progress. In 1969, NASA landed the first man on the moon. 40 years later, we have harnessed a more powerful computer in the palm of our hands, the smartphone, than NASA's entire computer infrastructure during that space moon landing.

    Whether or not you believe in evolution via nature, artificial evolution is undeniably apparent and easily observable in computing technologies, and big data is now at the forefront of the next step in its evolution.

  • Report this Comment On March 16, 2013, at 11:47 AM, kennyli89 wrote:

    I just realized my response looks more like a blog post than anything else.

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