Is higher education doing enough to equip students for a ‘Big Data’ world

Written by Luke Burns

DATA permeates most facets of modern living and its rapid growth now and in the future will have a huge bearing on graduate employment.  LITE Teaching Enhancement Project Leader, Dr Luke Burns, introduces his final project report here and asks if universities are doing enough to ensure students are equipped with the right skills.

We are awash with data, whether these be more traditional datasets such as school performance statistics or store revenue estimations or newer forms of what we now term ‘Big Data’.

These new and exciting datasets include social media interactions like Facebook check-ins or geolocated tweets and data generated from a wide range of daily activities such as loyalty card swipes, mobile phone usage, credit card spends and internet searches.

There is no doubt that we live in a data rich society so much so that 90% of the world’s data has been generated in the past two years, and that is one statistic that we should sit up and take notice of.


In my first blog I explore these new and emerging datasets in far more detail and, as a result, I began to introduce a changing face of in-need contemporary graduate skills.

This second blog takes the discussion forward.

With this avalanche of data comes many opportunities and challenges, particularly for higher education providers who market themselves as equipping graduates for modern society and cutting-edge employment.

The big question is – is this really happening?

Rapid innovation

‘Big Data’ has been described by many as ‘the new oil’.  This is a clever analogy as oil fails to carry any meaningful value unless refined correctly and the same can be said for the new forms of data we now encounter.

Having a lot of data is meaningless unless the skills are in place to handle, process and ultimately refine it, with a focus on quality.

Today’s graduates should be those with the skills to refine the data and turn it into public or commercial value.

Whilst it is clear that industry is moving forward at a rapid pace through data innovation, it is imperative that higher education does the same to ensure the supply of skilled graduates meets industry demands.

Keeping up

If one imagines a hypothetical line graph comprising two lines, the first representing industry innovation with data over time and the second being higher education’s innovation with the teaching of data and associated quantitative skills.

The line illustrating industry is not only positioned higher but also increasing at a far more rapid rate.

The line depicting the ability, and willingness, of higher education to innovate is far more plateaued with little upward movement over the past decade.

In simple terms, this hypothetical line graph highlights the problems facing the education sector.

Industry has the resource and motivation to innovate and whereas, in general education appears hamstrung and continues to educate students on the same tried and tested methods and techniques which have been taught for years.

Such skills are useful but are rapidly losing value in the competitive marketplace.


In order to explore the relationship between supply – of graduates – and demand, industry recruitment needs, my Teaching Enhancement Project was undertaken.

It goes without saying that exploring this relationship is a huge undertaking and hence a small project such as this only scratches the surface.

It does, however, provide substance and debate surrounding the issue and emphasises the problems faced.

If nothing else, it highlights the huge value in working with contemporary industry to design, implement and later audit curricula.

Skills audit

The organisations that took part in this research were asked about the core skills now required by graduates entering more technical and data-heavy roles.

All referred to an array of skills they would like to see as part of a graduate’s toolkit – which may or may not have been considered as part of present university curricula.

Skills and experiences such as an ability to automate processes, conduct rudimentary computer programming and clean and process ‘dirty’ and incomplete data were mentioned.

These skills are not commonplace in all curricula, often due to the rigid timetabling of education and therefore, often a perceived need to ‘teach’ content within a one or two hour weekly window.

This is a timeframe that does not easily allow for the introduction to incomplete or ‘dirty’ data due to a need to reach, and assess, an end product more quickly.

Differing opinion

Of course, subject variations do exist, particularly between STEM and social science disciplines.

Whilst those industries participating in this research also listed a range of other skills deemed core to gradate recruitment today, specific software packages such as Alteryx, Tableau, Hadoop and even Stata are commonplace in industry – but less so in higher education – were mentioned.

These packages are rarely available to students as part of their studies with a common explanation from universities being that education is about theory, process and technique and therefore software is irrelevant.

This argument does stand up but only providing that the process and technique taught are applicable to contemporary society and at present it appears that certain elements are not.


Full details of the work undertaken can be seen in the attached report of my LITE Completed projects page. 

The trends identified are generalised and not reflective of any specific degree programme or institution.

The trends do, however, highlight a growing disconnect between industry wants and education provision and whilst this gap is not insurmountable it does require a conscious effort by education providers to work with industry to design, implement and audit up-to-date curricula to ensure supply begins to close the gap with demand.