This is a guest post from Evanna Kearins, director of analytics, TIBCO Analytics
Harvard Business Review called data science the “sexiest” job of the 21st century, yet a survey conducted by the CBI warned that 39 percent of companies cannot find staff with the required skills and knowledge in science, technology, engineering and maths.
With the number of GCSE students studying IT-related subjects increasing, it is surprising to hear that student numbers for A-levels in computing and ICT have decreased. But whilst ICT is a subject that is helping to develop the skills data explorers need, other core subjects like Maths, English, History, Science and Business studies are also indirectly all helping to develop the next wave of data scientists and data explorers. The following core subjects being taught in schools are indirectly teaching students they skills they need to help fill the current skills gap:
ICT – The next generation is growing increasingly comfortable in using an array of devices and platforms. With the Internet of Things connecting devices, the volumes of data available are growing exponentially. In teaching children how to use platforms and understanding the nuances of each, they are also teaching fundamental skills needed by any data explorer.
Maths is another subject that can help students begin their career as a data scientist or explorer. Pupils are taught how to read charts and are able to gain a better understanding of comparing different patterns. These skills are not only needed in the class room, but by data explorers to make valuable business decisions as they seek to understand the data flowing through the organisation.
English – Being able to crunch numbers is important for a data explorer, but so too is having the ability to communicate the true value of this to the other board members. Communication is key in all walks of life so being taught English helps to translate numbers and data into meaningful insights that can transform the business. This is also crucial to bridge the gap between the business and IT functions.
History – Having an understanding of the past and how this will impact the future is also an important aspect. Just as students must analyse events in History, so must data scientists and data explorers. After all, past data trends can help shape the future through predictive analysis.
Science – Just like in an experiment whereby you have a hypothesis, methodology and then actively test for results, Science can help to identify what is fact vs. what is fiction. It is important to not just base data analysis on predictions. Understanding the difference between what the data says and what it actually means is a bit like a science experiment in itself!
Business studies – Interpreting the data is vital for any data scientist. But what happens to the data once it has been analysed? Through exploring the data and understanding the different areas of the business, data explorers should be able to identify how data analytics can impact every part of the business.
We are all now an intricate part of a new ICT ecosystem, one built on big data, apps and industry innovation. This is something that the graduates of today know better than anybody else. Making sure young people have the right skills may well be only half the battle, but there is a greater opportunity than ever before to build upon student interest, encourage the training of a wider skillset and help to find the innovators of the future who will play a valuable role in bridging the data scientist skills gap.