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The virtues of variety I


Big data variety, not volume, is the university challenge, says Chris Brown, data analytics consultant at OCF Most universities do now have


f you associate big data exclusively with large volumes of data, you wouldn’t be alone. A 2012 survey by


Harris Interactive of 154 companies found that nearly 70% used a volume-based definition for big data. Much like ‘cloud’, big data is a great headline grabber, but it gives off the wrong connotation – volume, volume and more volume. There has been, for many years, more


defining words for big data. Gartner analyst Doug Laney in 2001 first defined big data as management challenges thrown up in the three areas of volume, variety and velocity of data (the three Vs). And, of course since 2001, plenty of people have stepped forward escalating the big data definition up to seven Vs now. I certainly think greater use of these


types of definitions is a step in the right direction, to help universities begin to understand big data beter. The effect would be similar to exchanging the term ‘cloud’ for IaaS, PaaS, SaaS etc – these terms are now widely accepted. However, perhaps more importantly,


I’m of the belief that most of these current views are actually out of touch with modern universities. A September 2013 survey by supplier Steria suggested that only 8% of respondents felt that ‘scaling options’ relating to rapidly growing data volumes represents a serious problem. The majority of companies simply do not generate, want


or have access to petabytes of data. Big data volume really only applies to


a ‘few’ select organisations – the giants such as NASA, Tesco and Walmart. Sylvan H. Morley III, director of information lifecycle governance for IBM Worldwide, tends to agree: “I find a great deal of people who hear and can regurgitate the words ‘big data’ but if you listen to what they are saying what they mean is ‘a lot of data’ rather than the ‘big value of data’. I think this misses the point, if you look at the core of what ‘big data’ is really about; it’s about extracting value from data, the big ideas that data can provide or the big insights that data can bring that we weren’t geting before. So for me, ‘big data’ is about using only your valuable data; not just managing crushing amounts of data.” In the case of


the second original V (velocity) my issue is much the same, not every organisation requires the capability to stream petabytes of data in real time. It’s a requirement in 5–10% of organisations we come across (and not forgeting our heritage is working in the high performance computing industry).


a variety of data though – email, admission systems, library systems, lecture notes, images, social media feeds, audio, video, etc which are not aggregated and put to use. It’s ‘big’ in terms of its complexity and presents a real opportunity for universities to gain new insights to improve performance and profitability. Some of the most forward-thinking universities are already now analysing such information held in student retention and behaviour systems – because student retention can significantly boost a university’s financial situation. As suppliers and speaking to the wider industry, we need to take big data and break it down, so it’s more widely understood. Second, we really need to start pushing the benefits of big data variety aspect.


For universities out there who think big data doesn’t apply, ignore the headline-


grabbing name and start to think about all of the data variety siting idle. Pull this data together – transform and analyse to deliver improvements to your operations. ET


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