Data is being collected at an unprecedented speed and scale – but 'big data' is of little use without 'big insight'. The skills required to develop such insight are in short supply and the shortage of skilled workers in the data analytics market is cited as a key barrier.
The Data Science and Analytics MSc programme provides these skills, combining a strong academic programme with hands-on experience of leading commercial technology – and the chance to gain industry certification.
You will develop both your critical awareness of the state-of-the-art in data science and the practical skills that help you apply data science more effectively in the business, science and social world.
The programme is run in conjunction with SAS, a market leader in business analytics software and services, and the largest independent vendor in the business intelligence market.
Brunel's programme is unique in being the only current MSc programme that is fully integrated with SAS, providing the SAS base certification.
The Harvard Business Review calls data science the “sexiest job of the 21st century” – with demand for graduates with SAS skills rapidly rising across financial, retail and government sectors. Data science is now in vogue.
From government, social networks and ecommerce sites to sensors, smart meters and mobile networks, data is being collected at an unprecedented speed and scale – creating an expanding job market for qualified data analysts.
The practical aspects of many of the modules will allow you to gain hands-on experience of several commercial SAS tools (e.g. SAS BASE, Enterprise Guide, Enterprise Miner and Visual Analytics). This experience is designed, in part, to develop skills in preparation for the SAS certification part of the programme.
By the end of the course you should be able to:
- Comprehend the key concepts and nuances of the disciplines that need to be synthesised for effective data science.
- Demonstrate a critical understanding of the challenges and issues arising from taking heterogeneous data at volume and scale, understanding what it represents and turning that understanding into insight for business, scientific or social innovation (i.e. data science).
- Develop a practical understanding of the skills, tools and techniques necessary for the effective application of data science.
- Apply a practical understanding of data science to problems in social, business and scientific domains.
- Evaluate the effectiveness of applied data science in relation to the issues addressed.
As an integral part of the programme, you will gain hands-on experience of commercial SAS tools – SAS being the market leader in business analytics software and services, and the largest independent vendor in the business intelligence market. You will have the opportunity to obtain SAS certification (e.g. SAS Base Programming) which is a recognised industry qualification, following a two week SAS certification ‘boot camp’ preparation course.
From an industry perspective, there is an increasingly well-documented skills shortage developing in-and-around data science – as highlighted in the following reports and studies:
- “A shortage of skilled workers in the overall data analytics market is cited as one of the key barriers to further data analytics activity for businesses both globally and in the UK” (source: ‘Seizing the Data Opportunity: A Strategy for UK Data Capability' - 2013 UK government report.
- 46% of respondents in a global survey quoted staff shortages as the most common barrier to implementing data analytics (source: ‘Seizing the Data Opportunity: A Strategy for UK Data Capability', 2013 UK government report).
- Demand for big data staff is predicted to increase by between 13% and 23% per annum, between now and 2017 (source: E-skills UK).
- ‘The data scientist: the sexiest job of the 21st century’ (source: Harvard Business Review article, 2012).
- Businesses that outperform competitors are five times more likely to use analytics strategically than low performers (source: ‘Getting Serious About Analytics: Better Insights, Better Decisions, Better Outcomes’ - Accenture, April 2011).
- Organisations that invest in analytics could help generate £216 billion for the UK economy and create 58,000 new jobs over the next five years (source: Centre for Economics and Business Research report, ‘Data equity: Unlocking the value of big data’, April 2012).
Our Master's programmes aim to equip you with the qualities and transferable skills necessary for employment. Each course is developed with industry in mind and has one or more industrial advisers who are involved in course development and delivery.
The ability to generate effective insight and value from data is increasingly important across all industrial sectors. Data science is thus becoming a feature in a very wide range of industries, including automotive, banking and financial services, energy (e.g. oil and gas), health, management consulting, media and new media, retail and transport.
Given the range of vertical sectors that data science is important to, there are a vast number of companies seeking to employ graduates in this area. These include such organisations as Accenture, AstraZeneca, AXA Insurance, British Airways, Capgemini, Experian, FICO, GE Healthcare, HSBC, nPower, Orange, PayPal, Sopra and Waitrose.
The roles that our graduates are typically recruited to within these organisations include analytics consultant, big data engineer/scientist, business analyst, clinical data scientist, data design specialist, data scientists, developer/development engineer, enterprise/technical architect, forecast analyst, marketing/customer and/or insight analyst, quantitative analyst and web analyst.
Entry Criteria 2016/17
A UK first or second class Honours degree or equivalent internationally recognised and usually come from a scientific/engineering background and/or a numerate subject area.
Applicants with other qualifications with industrial experience (that is relevant to the subject area) may be considered and will assessed on an individual basis and industrial certifications may be taken into account (such as those provided by organisations such as Microsoft and Sun for example). Such applicants may be required to attend an interview.
Entry criteria are subject to review and change each academic year.
English Language Requirements
- IELTS: 6.5 (min 6 in all areas)
- Pearson: 58 (51 in all subscores)
- BrunELT: 65% (min 60% in all areas)
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Last updated October 17, 2017