The IT skills gap is not a new problem. For years now a lack of properly qualified and skilled analysts has hamstrung the industry at large. Yet now, thanks to the rush to adopt technologies such as AI and big data analytics, every month we hear more and more about how businesses lack the skills to implement them.
At the same time, the clamour and need to adopt those technologies is only growing stronger. This has led to these technologies failing to achieve their full potential, and even putting them perpetually out of reach for some companies.
There are a lot of reasons thrown around for explaining the current skills gap, ranging from businesses’ standards being set too high to an overreliance on highly paid multi-skilled contractors. For me, the root of the problem is that the available pool of properly trained and experienced analysts has not kept pace with the recent explosion of new technologies.
For businesses, being able to store, access and model data is only one part of the process. When they do not arm their people with the right skills to convert that data into actionable business intelligence, return on investment will continually fall short of projections, no matter how incredible the technology.
Put simply, if data really is going to be “the new oil” then we need more oil well drillers. One way to manage this is to turn to the aforementioned multi-skilled contractors, who are naturally expensive and in high demand.
Another way is to upskill current employees, but this can be a long process and once they have been re-assigned, their old responsibilities will still need filling, moving the problem down the line. What is needed is a focus on creating a data literate workforce from the entry level up.
This is what the Data School aims to achieve, offering a training programme for the next generation of aspiring data scientists, teaching them the skills they need to succeed using tools such as Tableau, Alteryx and EXASOL.
Over the last five years, the team at The Information Lab has trained thousands of people on these tools, and for the last two and a half years we have been providing four months of focused training from some of the best trainers in the world. This gives trainees a deep understanding of how to store, manage, prepare and visualise data in a business setting.
In addition to this, the Data School strives to maintain a 50/50 gender split in all of its cohorts; bridging the IT industry’s gender gap is a vital step towards bridging the growing skills gap.
It also teaches students the soft skills required for demonstrating the value of big data analytics, which is why each aspiring data scientist or analyst we train is required to create at least one presentation based on a different data set every week.
One of the biggest problems facing companies trying to incorporate data analytics into their business practices is drawing out actionable insights from the data they gather, and being able to explain it is an important part of demonstrating the value of big data when not everyone within a business is tech literate.
While learning both the hard and soft skills, there is no substitute for experience. This is why all trainees take part in company placements as part of the programme, experiencing the practical reality of working within an organisation. These placements can vary from analytic centric businesses like in-memory database analytics provider EXASOL, to small companies only beginning to experiment with what they can do with their data.
This holistic approach offered by the Data School is only one measure being taken by the industry to address its yawning skills gap. Government initiatives offering grants to help close the gap, and companies offering increased internal training to existing staff, will go some way to plugging the gap as it stands currently.
However, as the industry continues to grow so too will the gap, continuing to outpace the rate of new skilled individuals coming in. Only when we have created a data literate workforce from the ground up will we see the digital economy realise its potential.