The ‘data revolution’ is one of the defining developments of the 21st century. But to participate in this revolution organisations need people with the skills to manage, analyse, interpret and communicate data, in order to extract insight and value. The University of Sheffield’s Data Science MSc aims to teach these skills...

What one aspect of the MSc Data Science course do you personally look forward to each year, and why?

‘The MSc Data Science is a new programme. In developing the curriculum I have really enjoyed collaborating with external organisations on relating Data Science theory to practice and building these elements into the programme. There are two external organisations who are very actively involved in the programme. The first, Peak Indicators are a UK-based Business Intelligence (BI) company with experience in developing BI solutions using Oracle and Endeca products.  The second is Intranet Focus, an information management consultancy firm run by one of our visiting professors at the Information School. Both organisations have links to industry experts who will be invited to contribute to the Data Science course in a number of ways, including participation at an ‘Industry Day’ and involvement in developing case studies to show Data Science in action.

A further aspect of the course that I am looking forward to is how data can be analysed to identify interesting and previously unseen patterns. Students will learn how techniques from data mining and data visualisation can be used to extract information and knowledge from datasets. A particular challenge will be teaching more technical content in a way that students from a variety of backgrounds can find accessible and relate to.’

Tell us a bit about the faculty or staff in the department, and where they come from.

‘Our staff have very strong links with the profession through research collaborations, memberships on professional bodies, and in some cases they have had previous careers in professional organisations. They come from many different subject backgrounds: English, social science, library and information science, chemistry, computer science and health so that it’s a truly “interdisciplinary” department. Our teaching is linked closely to our active research interests. That makes it a really stimulating place to study. There are lots of fascinating perspectives on current issues. Because we are a small department students really get a chance to know and talk to staff. We have staff who have come from all over the world, including the Far East and North America and have been through the experience of coming to the UK, so can relate to students who are taking on a course in another country.’

What are the benefits of studying Data Science at the University of Sheffield?

‘The Information School at Sheffield is the top department of our type in the UK. In every Research Assessment Exercise (RAE) we have been top and in the 2014 Research Excellence Framework (REF) we were rated number one for research environment in the UK. The School was the first UK school to join the iSchools organisation (ischools.org) which is an international club of information schools. This year it will have existed for 50 years. The concept of the Sheffield Graduate articulates very neatly some of the key attributes someone will take from their degree.’

Why is it an exciting time for prospective students to move into the Data Science field?

‘A recent report by the e-Skills UK and SAS highlights that the demand for Big Data skills is expected to rise 92% over the next five years. Organisations are increasingly in need of ‘data savvy managers’ – people who can manage and support data-driven decision-making. This need will be met by people acquiring skills in three core areas: data management (storage and linking), data analysis (including data literacy) and business and policy insight (context awareness); all of which we will be teaching on the MSc Data Science programme.

Many of the Data Science programmes from other institutions are strongly focused on the underlying technologies and require in-depth knowledge of computer science. What makes the Sheffield course distinctive is that it will help students to develop their uunderstanding of the theory and practice of Data Science and its application within organisational contexts. Students will gain hands-on experience with data analysis, as well as more theoretical topics in Data Science and awareness of wider issues, such as privacy and ethics of using data and the need to combine a variety of approaches (both quantitative and qualitative) when analysing and interpreting data.’

What is Big Data?

‘The term ‘Big Data’ is commonly used to refer to data with the following characteristics (the 4 Vs): volume (the amount of data being generated), variety (the range of data types and sources, including structured and unstructured data), velocity (the rate at which data is collected, shared and analysed), and veracity (the reliability of data). Numerous opportunities exist for Big Data including increasing operational efficiency, better customer service and identifying new markets. In addition there are clear benefits for society at large in areas such local government and healthcare. The challenges of utilising Big Data effectively include technological issues, analysing large datasets, collecting data from reliable sources and privacy.’  

Can you give a few examples of the roles and positions which graduates have gone onto?

‘The programme started in September 2014 so our first cohort of students will complete their degrees this summer. The skills and qualities gained throughout the Data Science programme, however, should help prepare students for a range of jobs within data management and analysis. However opportunities will be available in Public, Private and Not-for-profit organisations where the focus is on driving value out of their data assets. Post qualification roles could be business-focused, including Business Analyst, Business Intelligence Analyst; or data-focused, including Data Scientist/Engineer, Data Manager, Data Analyst, Data Architect, Data Modelling and Data Mining Engineer.

Data Science is applicable to a wide range of sectors and related jobs can come up in unusual places. For example, a recent job advert from the National History Museum (London, UK) was for a Data and Information Architect to “take a leading role in its digital science mission: to collate and organise the data of one of the most important Natural History collections in the world and make it openly accessible online. The post holder will design and implement digital data models, systems, practices and processes for the effective management of our scientific data within a world-leading institution with over 250 scientists and 80 million specimens.” The job specification for the role included many of the skills taught in our Data Science programme.’