Big data is a buzzword that’s been around for a while now, and – if anything – its reputation is just as big as the amounts of info it involves. The term is used across many different industries and, according to LinkedIn, data scientist was the most sought after job of 2014; but whilst the data is big, there is still very little understanding about what it actually is, and how businesses can use it effectively.
Big data essentially refers to large quantities of data that are too big and complex to be processed using traditional data processing applications. As you might imagine, having that amount of info at your disposal can be very useful, if it’s relevant and used wisely.
Big data analysis is handy for things like helping prevent diseases, fight crime (kinda like a less lycra’d superhero) and obviously, find trends for businesses – but many aren’t capitalising on the information. At our recent round table, Danny Franks of SBS networks said: “I don’t think the majority of SMEs understand the majority of data that they’ve got. I don’t think they realise what a resource they’ve got to tap into and how they can use it.” Basically, what businesses need to do is pull the trends together and find bits that they can use to sell and support their services.
For example, if you’re a hospital you might look at mass amounts of data to help predict which patients are likely to be readmitted within a short period of time to help prevent expensive readmissions; or a retailer could look at social media to see customer preferences and product perception. There are so may options, and as the data out there grows, the possibilities will too.
In 2012 Gartner analyst Doug Laney helped break down big data into three Vs: “Big data is high volume, high velocity – how fast it’s processed and analysed – and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization – we’re constantly updating.” This has become a fairly common way of describing big D. Veracity was also added, to indicate the quality of the data being analysed, and variability, which refers to inconsistencies within the data.
It’s even starting to be used in a whole range of areas that you wouldn’t necessarily expect, from sports – to help teams and sportspeople track sales and improve strategies – to health care; for example, in gene sequencing, which could help stop the spread of epidemics through knowing more about the disease and how to treat it.
Not only does it pay off in these more global platforms, it pays on a personal and business level too. Data scientists make over $123,000 per year on average, and it’s on the rise; and companies are desperate to hire people with data science skills statistical analysis and data mining skills. Big data-related talents account for a third of the top-15 most wanted skills this year, taking the crown from 2013’s top job – social media marketing.
It’s not all great though, and there are some that aren’t on board with big data – some don’t think the way we analyse the data is right, and some aren’t sure it’s an effective way of gathering info full stop. Others say it’s quantity over quality or that it’s just not representative (e.g. if you got info from Twitter, it’s a platform that isn’t representative of the whole population).
But – assuming that, in our data-hungry world, it’s here to stay – how can companies prep themselves for the dawn of big data? Well, for a start, by ensuring that all their employees are able to decipher data, with a wide range of knowledge and skills so they can analyse what they’re seeing (fairly useless having all this info and no one to untangle it). It’s also important to make sure the data is organised and stored effectively; and on a lower level, to make sure the little data going in is right, or the big data definitely won’t work.
At the end of the day, there’s no need for companies to be afraid of big data, but – as the big data trend just keeps on getting bigger – we need to make sure we’re doing it right, in order to create the biggest opportunities!
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