Source: University World News
There are gaping holes in data analysis skills training which should be addressed by an upgrading of data analysis and skills provision at schools and universities, according to two new reports.
Across various sectors, collecting and analysing quantitative data is becoming increasingly important – and the need for workers able to analyse and interpret datasets is expanding exponentially. Yet employers battle to find candidates in these fields.
A joint policy briefing released last week from Nesta and Universities UK, drawing on two research reports on supply and demand for analytical skills in the UK, recommends a kite marking system to identify relevant courses to prospective university applicants and employers. It also calls for the embedding of quantitative analysis skills across university disciplines.
The findings are contained in Analytic Britain: Securing the right skills for the data-driven economy (Nesta) and Making the most of data: Data skills training in English universities (Universities UK).
At least 35% of British jobs are at high risk from automation, according to a recent Deloitte report. Thanks to technological advances, lower-skilled jobs like those requiring repetitive processing might disappear, with clerical and support services possibly being replaced by roles requiring digital, data management and creative skills.
“As data use increases, a sufficient supply of data skills becomes critical to the labour force,” said Professor Sir Ian Diamond, principal and vice-chancellor of the University of Aberdeen, chair of the Universities UK Data Skills Steering Group, and research leader on Making the most of data: Data skills training in English universities.
Universities play an important role
“Universities have played – and will continue to play – an important part in the data agenda. They allow for the opportunities presented by data to be realised and exploited, propelling technological advancements and spreading analytical skills. Universities also play an important part in overcoming some of the challenges associated with data, such as capability issues, skills shortages, and the ethical and legal issues posed by increased data usage.”
Training in data analytics is found in most science, technology, engineering and mathematics, or STEM, and social science courses, he added, yet the extent of provision varies by institution and degree subject. “To meet the current and future needs of our economy, more must be done to embed data skills as an essential component of many degrees. All social science graduates should be able to conduct quantitative research in their fields.”
The data skills shortage is not characterised only by an absence of recruits with the right technical skills, but by an absence of recruits with the right skills combination. Often, more advanced data analysis is taught in some subjects than in others, and there is variation in the extent of data analysis teaching between similar courses at different institutions. Occasionally, data analysis is isolated from the main curriculum.
Other challenges include students lacking basic skills in maths and computational skills; a shortage of academic staff confident about teaching data analytics, and limitations on what can be taught within a three-year curriculum.
Steps are being taken, however, to remedy the situation. The report said many universities were collaborating with employers to offer work placements for undergraduates and in the development of curricula; the government had developed a schools coding curriculum to support the early development of programming skills; and statistics, including software use to explore real large datasets, will become a compulsory part of A-level maths under a new specification for the subject from 2017.
Stronger teaching of mathematics and statistics in schools and colleges was imperative, and access to information about career opportunities for data analysts should be broadened. Awareness of the value for business data should be raised, the researchers recommending a targeted campaign via the government’s Great Business website for this purpose.
Other recommendations included embedding data analytics in other school subjects and developing extracurricular data activities at schools and colleges; and in universities and in vocational education fields, increasing the supply of high-end analytical talent by embedding quantitative analysis across disciplines. It was also recommended that skills development programmes and interdisciplinary research be fostered.
The labour market should also step up to the plate by creating a cross-cutting taskforce around data analytics; actively convening industry and community analytics networks, and supporting innovative interventions enabling local authorities to boost analytical skills.
Diamond said there was a need to support interdisciplinary, innovative research projects involving advanced data analytics, statistics and quantitative skills, which means cross research council collaboration and funding.
“We recommend a top slice of the RCUK (Research Councils UK) budget to establish a strategic fund through which interdisciplinary research is funded. RCUK could take a strategic and convening role in this space.”
He said the technical complexity of working with what is often termed “big data” is well recognised.
“New technologies and methodologies allow for the collection of increasingly large datasets. This has led to new opportunities across all disciplines, from astrophysics to zoology, genome sequencing to business analytics. These large datasets are often unstructured, dynamic or both. Data may be incomplete or corrupted. These characteristics represent a challenge to analysts.”
The report said to meet current and future demand for data skills, collaboration between schools, universities, employers and policy-makers will be crucial, to define what core skills are needed and embed them in a framework of skills development and progression.