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Intel beckons SMBs aboard Big Data bandwagon

Small fry firms can be Big Data fish with Hadoop

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Cutting edge Big Data projects might seem the sole preserve of big name multinationals and government organisations but the democratisation of these next gen analytics capabilities is coming soon to an SMB near you, according to Intel.

Speaking at the APAC launch of the Intel Distribution for Apache Hadoop, Chipzilla’s global director of enterprise computing, Patrick Buddenbaum, told The Reg that the firm’s OEMs, SIs and software vendors will help to push analytics capabilities down to a wider base of organisations than might currently be using such advanced tools.

“The partner and ecosystem aspect will drive the scale of this thing to the next set of customers – software vendors incorporating Hadoop into their packaged ERP or BI applications,” he said.

The “other element of the dissemination curve” lies with cloud players like Amazon and Savvis effectively offering Hadoop-as-a-service – giving yet more firms the opportunity to experiment with the tech, added Buddenbaum.

It will happen “over time, not over night”, and a range of business, technical and cultural issues may slow the rate of adoption of such capabilities among small and medium sized firms, he said.

OEMs and SIs can help customers unfamiliar dealing with large scale clusters. However, many companies aren’t asking the right “what if” questions of their data, while elsewhere CIOs are failing to support requests for broader cross-organisational data access to generate real-time intelligence, said Buddenbaum.

Intel was also at pains to point out its Hadoop distribution is not the “be all and end all” and that Apache Hadoop itself is not the answer to all Big Data problems but just “one piece of the puzzle”.

However, Forrester research director Dane Anderson was more positive, arguing that the Hadoop-based distributed computing paradigm is already collapsing Big Data barriers to entry for smaller firms.

“A lot of what is holding large companies back is that it’s hard for them to change. The majority of analytics spend is in the traditional, data warehousing / batch processing way of analysis,” he explained.

“Vendors and enterprises overseeing that don’t want to let it go but there’s a new, younger shift based on Hadoop and open source. We have generational change and the possibility of a lot of companies coming in and transforming their industries with this technology.”

The focus will shift towards this idea of “cutting edge compute and software resources at pay-per-use prices” using Hadooop, but it will take time according to Anderson, who referenced the 5-6 years it took for SaaS to hit the mainstream after getting a foot in the door among early adopters.

He highlighted a dearth of in-house skills, organisational roadblocks and lack of clear ownership on Big Data projects, as well as the problems of navigating vendor hype, as key additional barriers.

As it is, at the moment there are few case studies for Big Data being bandied around by the major IT players that aren’t large scale projects such as Intel’s work with the world's biggest network operator, China Mobile - designed to give customers real-time access to billing data.

However, Chipzilla’s APAC marketing bod Takashi Tokunaga said the firm was working with several sub-100 employee online retailers in the region who have been harnessing Hadoop to help customise and enhance the shopping experience à la Amazon.

Another example comes from EMC and research outfit the Singapore-MIT Alliance for Research and Technology which embarked on a project to discover why the long queues for taxis in Singapore when it rains.

After crunching weather satellite data and GPS data on local taxis, they discovered that it wasn't because cabs were more in demand at these times but because drivers were refusing fares in the wet because of the risk of accidents, which they were liable to pay an upfront $800 fee to cover.

In a few years, as the hype blows away and adoption goes mainstream the industry will probably not even be talking about “Big Data” anymore but just "data analytics".

However, if it means always being able to grab a taxi, even in the middle of a thunderstorm, this may yet be one of the few technology trends which just about lives up to the hype. ®

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