The last decade has seen bigger and faster developments in the technology space than the world experienced in the past century, and this is permeating right the way through to the education programmes and approaches that are shaping our business leaders, doctors and scientists of tomorrow.
In terms of the technology space, big data solutions are quickly becoming one of the most important overall areas. As such, the science behind this relatively new field is gathering pace rapidly, so there has never been a better time to pursue a career in data science career, and the latent data insights have never been so potentially valuable.
Much of the current enthusiasm for data science focuses on technologies that simplify the data interpretation process and the related open-source tools applicable for cloud computing, and visualisation environments. While these are all important breakthroughs, the people with the skill and mindset to put them to good use are by far and away the most valuable asset.
Data science has one foot squarely in the world of statistics and linear algebra, which are the sorts of applied mathematical skills, but in practicality it is a several steps down the evolutionary line.
While applied maths and statistics have been taught in schools for a long time now, the increasing size of the data and the complexity of tools required by statisticians and critical thinkers will require them to learn skills to deal with these multifaceted data systems, and gain the knowledge of complex software practices too.
The data scientist will be a crucial element for many companies across all manner of verticals in years to come, key to performing mission critical functions such as; running A/B” testing of platforms for apps or websites; analysing A/B” tests with specific business or product objectives in mind; building recommendation engines and tuning their algorithms; building fraud detection systems; predict customer churn rates for subscription based industries like Mobile Network Operators; and even running historical statistical analysis on customer shopping behaviour.
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As companies increasingly look to find new value from their existing assets and differentiate themselves in crowded and competitive markets, the place of the data scientist to business strategy and objectives is becoming pivotal.
And as demand outstrips supply, a shortage of data science exponents is becoming a serious constraint in many different sectors.
In just over a decade we have transitioned from a relatively data-scarce world, to a data-rich world, where the amount of data available is already virtually limitless and doubling almost every other year. The call to action is clear enough: we need data scientists now, just like we continue to need physicists, chemists and biologists.
There is good news however. August saw a record high, with the number of students taking STEM A-levels increasing by more than 38,000 since 2010. Similarly, computer sciences applications at university were up a staggering 13 per cent, to 97,110 the greatest percentage increase of any of the other top ten most studied subjects.
This is good news for British businesses looking to build todays workforces with a view to the business demands of the future, and more data scientists will clearly come from this increasing pool of talent.
The advance of big data shows no signs of slowing down, and schools, colleges and universities are beginning to wake up to this demand for more members of the work force with data science skills.
Over the next decade we can expect to see growing investment and interest from all levels of the education spectrum in developing data science as a true standalone subject, and investments like that of the University of Michigan, which is set to invest $100m over the next five years in a new data science initiative, will increasingly become the norm.
If British businesses are to remain competitive in global markets they, and the education system that underpins the workforce, must recognise data science as not just a gimmick, but rather an integral part of business strategy and wider education agendas.
Sean Owen is director of data science at software firm Cloudera