As UK businesses look to exploit the massive explosion of big data to support evidence-based decisions relating to sales, it's becoming evermore apparent that they're going to need to hire staff with the right big data skills; data scientists.
This is good news for anyone studying data at university, as their skills will be in high demand and it's suggested that graduates will receive a starting salary of up to £32,000, which is a £6,500 head start on the average starting salary of £25,500.
Since 2011, university applications in the UK have fallen by 4.2%, as an increasing number of school leavers shun a university education in favour of apprenticeships or immediate employment. However, the Government's 'Strategy for UK Data Capability' published earlier this month recognises the need for Government strategy in this sector.
Meghan Kelly, technology writer on website VentureBeat.com, recently penned an article claiming that "between 2010 and 2020, the data scientist career path is projected to increase by 18.7%, beaten only by video game designers. The Big Data industry is expected to be a $53.4bn industry by 2016.
"Given that job posting for data scientists increased 15,000% between 2011 and 2012 alone, according to FICO, if you're not looking for a career as a data scientist, then maybe you should be."
But can the demand really live up to the hype?
Chris Taylor from TIBCO doesn't think so. Writing on Wired.com, Taylor responds to Kelly by saying: "The first reason Kelly has it wrong has to do with the snapshot in time she's choosing: 2011 to 2012. When the hype around big data kicked into high gear a couple of years ago and we invented the word "data scientist", we were breaking new ground. The job's high level of attention is a factor of its newness more than its explosive growth. 1500% growth can be as simple as going from one to 1500. It isn't quite that simple, but you get the point."
Back in the UK, Brunel University recently hosted the SAS Careers Fair, putting 300 students from 15 universities in direct contact with SAS customers including Barclays, British Airways and Nationwide. Between them these businesses have more than 100 graduate vacancies for data analysts.
However, various insiders and critics are saying that by the time the majority of these students graduate from university, their places in the world of Big Data may have already been filled - by software applications and tools.
Taylor says: "We're in a phase where front-end applications are scrambling to catch up with the relatively new found capability to distribute storage and processing across many machines (Hadoop clusters, for example). Hadoop is not a polished application with clean interfaces. For now, it takes coder/analytics people to run it well, thus the need for data scientists ... for now.
"However, a new breed of applications are launching now that allow business users to create their own big data applications in the cloud with a much lower level of IT and data scientist support. The future looks like data scientists working at software companies that sell to many customers, much like finance, marketing and supply chain applications products that mask complexity and sell broadly.
"If you're very early in the game, there's still time to get where you need to be, but perhaps your focus should be on the myriad of ways to collect, move, refresh, use and govern data in general. The data discovery tools need to sit atop this foundation and if you don't have it, a team of data scientists may not be your next move.
"If you're a company convinced that you need to hire a score of data scientists, be careful. There's a pretty high likelihood that by the time to recruit, hire and put those data scientists to work, someone will be selling tools that reduce the complexity and cost of what your team does. There will obviously be exceptions to this rule, but it's worth tempering some of that recruiting enthusiasm with some skepticism for the hype."
CBR spoke to Frank Buytendijk, a Gartner analyst based in Amsterdam, and put forward the argument that soon we may see software applications replacing the role of data scientists and others whose work revolved around Big Data. He says: "That's exactly what I am worried about. [But] as much as tools can handle complex analytics, they don't take away the need to actually understand what you are doing. Analytical power needs to be harnessed. If done in tools for end-users, there will not be a lot of flexibility.
If done in a flexible way, it requires statistical knowledge. Tools, which are easier to use, and require less programming, will make the data scientists more productive, not replace their need. The thought alone of organisations thinking this, or software vendors claiming this would make me rather nervous.
"For the years to come, we [have] seen at least three times the demand for data scientists as there is supply. A recent survey showed that most organisations believe they can handle building those skills themselves, and feel less need to hire experienced people, work with universities or consultants. We believe this means organisations are underestimating the complexity. Not of the technology, but of the skills themselves."
Indeed, he's correct, at least about the demand. In the UK, recent research has shown that three out of five large UK organisations are finding it challenging to hire people with the specialist big data skills they need. Demand for big data specialists is expected to rise by 243% over the next five years, to around 69,000 people.
Liam Fox MP, speaking at the SAS careers fair, says: "The global information economy represents an opportunity for the UK to take a leading role, where sourcing individuals with the relevant skills is imperative. For this to happen it's vital that Government, industry and universities all work together to ensure that graduates leave university with the skills the economy needs."
The UK government's information economy strategy announced earlier this year stated: "Business sectors across the economy are being transformed by data, analytics, and modelling. The UK now has the opportunity to take a lead in the global efforts to deal with the volume, velocity and variety of data created each day."
For the time being, getting into data analytics would seem to be a wise choice for anyone off to university or perhaps thinking about switching careers. Only time will tell if in the near future there'll be an abundance of redundant data scientists, but my money's with Frank. What with the billions of connected devices due before the decade is out and APIs opening left right and centre, that data is going to keep flowing and there will only ever be more.