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Power of Big Data for SMEs

by Dan Gray
February 27, 2014
in Uncategorized
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A recent study by SAS on Adoption and Employments trends of Big Data Analytics found that Small and medium-sized (SMEs) businesses in the UK are largely unaware of the opportunity that Big Data presents. SMEs were generally found to be intimidated by the costs and complexities of dealing with large amounts of data. Phil Simon (author of  Too Big to Ignore: The Business Case for Big Data) notes that there some data poor SMEs out there who are not really aware of the possibility to leverage the value of Big Data without brekaing their budgets. While at the same time Simon notes, there are some (SMEs) out there who are already doing interesting things with data without speding much budget on it.

SMEs which have risen to leveraging the value of Big Data are using services such as cloud computing and open-source software to realise various goals. At the same time, they are keeping in loop with the new cheaper ways to learn from data that are emerging with time. Phil Simon cites example of Kaggle, Acxiom and DataLogix as companies which are already  offering valued inexpensive Big Data services to SMEs.

Kaggle – a company which seeks to make data science an affordable fun sport. It offers crowdsourcing , social network, wiki, and job board opportuities on one portal, easy to be eased by SMEs lacking tech and data savvy talent.

Acxiom and DataLogix – are data brokers which provide SMEs with highly valuable data at reasonable prices. For example these data brokers obtain names of expectant parents and families with newborns from Experian (a marketing-services unit of credit reporting giant ) and sell it to relevant SMEs.

Phil notes that a lot of new ventures are jumping on the bandwagon to provide valuable Big Data services to SMEs. Not that these small big data ventures would replace the bigger corporations but they would offer the affordable to the ones who need it – the SMEs.


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Tags: AcxiomBig Data ImpactDataLogixKagglePhil SimonPower of Big DataSME

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