Masters Degrees (Sas)

About the course

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.

Aims

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.

Course Content

Your studies on the course will cover the modules listed below. 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). That experience is designed, in part, to develop skills for the SAS certification that partners the programme.

Typical Modules:

Digital Innovation
Quantitative Data Analysis
High Performance Computational Infrastructures
Systems Project Management
Big Data Analytics
Research Methods
Data Visualisation
Learning Development Project
Dissertation

Special Features

SAS Certification
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.

Women in Engineering and Computing Programme

Brunel’s Women in Engineering and Computing mentoring scheme provides our female students with invaluable help and support from their industry mentors.

Teaching

Module are typically presented in a mixture of lecture and seminar/lab format. However, where appropriate other teaching methods will also be incorporated. All our learning environments are supported by the market leader in Virtual Learning Environments (VLE), the BlackboardLearn system.

Assessment

Your learning will be evaluated through a combination of in module assessments and more traditional exams, with module specific assessments – for example, presentations within the Learning Development Project.

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About the course

Data Analytics MSc has been developed in collaboration with SAS; a world leader in data analytics. Due to this strong partnership you will gain substantial SAS software skills as part of your study. This course is designed specifically to equip you with the skills and abilities to address the skills shortage in industry. On successful completion of the course you will have developed your analytic and technical knowledge, and enhanced your professional skills within a Business Intelligence context. Upon graduating you will be prepared to undertake business intelligence and data mining roles within any target industry

Reasons to study:

• Taught by SAS accredited teaching staff

you will be taught by experienced SAS accredited teaching staff providing you with expert knowledge and skills

• Developed to fill skills shortage

course content has been developed to enhance your employability and gain substantial knowledge and equipping you with the skills required in for the use of the SAS software as well as Hadoop Distributed File System (HDFS) in industry

• 50 years history of research and teaching in computing technology

benefit from our well established academic expertise and advance your skills in, and knowledge of, data analytics to business problems

• Industry placement opportunity

you can chose to undertake a year-long work placement gaining valuable experience and skills as well as networking opportunities to build your industry contacts

• Excellent graduate prospects

equipped with the relevant skills for business intelligence and data mining roles including SAS Programming, Database Design and Business Intelligence

Course Structure

Modules

First semester

• Statistics

• Fundamentals of Business Intelligence Systems

• Research Methods

• Data Warehouse Design and OLAP

Second semester

• Analytics Programming

• Business Intelligence Systems

Application and Development

• Big Data Analytics

• Data Mining

Third semester

• Individual project

Teaching and Assessment

Teaching will normally be delivered through formal lectures, informal seminars, tutorials, workshops, discussions and e-learning packages. Assessment will usually be carried out through a combination of individual and group work, presentations, reports, projects and exams.

The course is run in association with SAS, the leading independent vendor in the business intelligence industry, and you will gain substantial SAS software skills as part of your study.

First semester modules provide you with fundamental abilities in the use of statistics so that you can gain insights and practice of using business intelligence systems and analytics programming to exploit multidimensional data sets.

In the second semester you are exposed to a variety of business intelligence systems, including those that use big data and data mining techniques. A further module prepares students to undertake an individual research project. This project module allows you to undertake extensive research into an aspect of big data, and/or provides an opportunity to develop and demonstrate your analytical and processing abilities in response to a given practical problem.

Contact and learning hours

You will normally attend 3 hours of timetabled taught sessions each week for each module undertaken during term time, for full time study this would be 12 hours per week during term time. You are expected to undertake around 24 further hours of independent study and assignments as required per week.

Industry Association

The Data Analytics MSc was developed and is run in conjunction with SAS. SAS is the world's largest independent business analytics company. It provides an integrated set of software products and services to more than 45,000 customer sites in 118 countries. Across the globe, both the public and private sector use SAS software to assist in their efforts to compete and excel in a climate of unprecedented economic uncertainty and globalization.

To find out more

To learn more about this course and DMU, visit our website:

Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

Applying for a postgraduate course:

http://www.dmu.ac.uk/study/postgraduate-study/entry-criteria-and-how-to-apply/entry-criteria-and-how-to-apply.aspx

Funding for postgraduate students:

http://www.dmu.ac.uk/study/postgraduate-study/postgraduate-funding-2017-18/postgraduate-funding-2017-18.aspx

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Have you ever noticed the adverts down the side of your Facebook page or received an email promoting a product you were 'looking for'? Do you wonder how this happens? Business intelligence and the insight it provides is now at the forefront of driving companies' strategic decisions. It's vital for businesses to understand their performance but, more importantly, identify their future potential.

This course teaches you to utilise data that is available to an organisation and present this information in an accessible format which will enable decision makers within a company to plan for the future.

You will study modules that are accredited by SAS - an industry leader in developing business intelligence tools - and this unique relationship will build your knowledge of their systems, enhancing your skillset to analyse data.

Whether it's to improve products, processes, consumer relationships or target customers - firms across all industries and managers across all departments benefit from good business intelligence. We will equip you with the skills to analyse data systems, advise colleagues and take a leading role in shaping a company's decisions.

You will graduate with the ability to understand the data and its sources, design and implement a data warehouse, and be able to act upon this information to support the business strategy planning. We will develop your skills in predictive analysis, report writing, identifying patterns, and how outside factors and current issues can affect the findings.

- Research Excellence Framework 2014: our University demonstrated strength in five emerging areas of research which it entered into the assessment for the first time, including computer science.

Visit the website http://courses.leedsbeckett.ac.uk/businessintelligencesas_msc

Mature Applicants

Our University welcomes applications from mature applicants who demonstrate academic potential. We usually require some evidence of recent academic study, for example completion of an access course, however recent relevant work experience may also be considered. Please note that for some of our professional courses all applicants will need to meet the specified entry criteria and in these cases work experience cannot be considered in lieu.

If you wish to apply through this route you should refer to our University Recognition of Prior Learning policy that is available on our website (http://www.leedsbeckett.ac.uk/studenthub/recognition-of-prior-learning.htm).

Please note that all applicants to our University are required to meet our standard English language requirement of GCSE grade C or equivalent, variations to this will be listed on the individual course entry requirements.

Careers

Whether it's retail, insurance, banking, education, hospitals, police, medical research or the military - you will have the skills to help lead any business in any industry that uses business intelligence to make strategic decisions. If you already work in industry, possibly as a programmer or in IT, our course will help facilitate your career progression.

- Business Intelligence Analyst
- Test Consultant
- NHS Analytical Support Officer
- Corporate Performance Analyst

Careers advice:
The dedicated Jobs and Careers team offers expert advice and a host of resources to help you choose and gain employment. Whether you're in your first or final year, you can speak to members of staff from our Careers Office who can offer you advice from writing a CV to searching for jobs.

Visit the careers site - https://www.leedsbeckett.ac.uk/employability/jobs-careers-support.htm

Course Benefits

The NHS, banks and police are among those who already use SAS system tools, and you will have the opportunity to take the SAS test, a chance to become accredited to work on their systems.

SAS want to see a higher number of business intelligence graduates who possess more than just a background in maths and statistics - they also want strong computing skills. You will be one such graduate.

Guest speakers from the business intelligence industry will also improve your knowledge and understanding of how data can be used by companies to plan their next business move.

Professor Mohammad Dastbaz

Dean, Faculty of Arts, Environment and Technology

"We aim to provide innovation in curriculum, engagement with current industry practices and standards, and to give our students the experience of working with staff whose research has national and international reputation."

Mohammad is responsible for the strategic leadership of the Faculty of Arts, Environment and Technology,having joined our University in June 2011 from the University of East London. A well published researcher, with over 50 refereed conference and Journal publications, his research profile includes many funded research programmes including JISC and EU FP7 projects. Mohammad’s first degree was in Electrical and Electronic Engineering. He then went on to complete a PhD in the 'Design, Development and Evaluation of Multimedia Based Learning Systems' at Kingston University. In 1989 he set up one of the UK's first multimedia PC companies, 'Systems 2000'.

Facilities

- Library
Our Library is one of the only university libraries in the UK open 24/7 every day of the year. However you like to study, our Library has you covered with group study, silent study, extensive e-learning resources and PC suites.

- Headingley Campus
Broadcasting Place provides students with creative and contemporary learning environments, is packed with the latest technology and is a focal point for new and innovative thinking in the city.

Find out how to apply here - http://www.leedsbeckett.ac.uk/postgraduate/how-to-apply/

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About the course

This course was developed and is run in conjunction with SAS, it will provide you with the knowledge and skills to effectively research, develop and apply business intelligence systems. These are computerised information systems which support an organisation in the decision making process. Many of the techniques used in this area are underpinned by predictive statistics and mathematical modelling. This course will emphasise the concepts and techniques of business intelligence systems and their application and development. You will have access to specialist computing laboratories including one suite reserved specifically for postgraduate students. Upon graduating you be well placed to take up more general management and business information systems development roles within industry, or to undertake academic researchin this field.

Reasons to study:

• Taught by SAS accredited teaching staff

you will be taught by experienced SAS accredited teaching staff providing you with expert knowledge and skills allowing you to work toward your SAS accreditation

• SAS endorsed course

enhance your employability and gain substantial knowledge and skills in SAS business intelligence software leading towards SAS data miner accreditation

• 50 years history of research and teaching in computing technology

benefit from our well established academic expertise and advance your skills in, and knowledge of, developing business intelligence systems and data mining solutions to business problems

• Gain an insight into real world solutions

attend guest lectures and seminars, which will give you a real understanding of the impact of their work

• Excellent graduate prospects

graduates have gone into roles such as BI/SQL developers, logistics data modeller’s and insight analysts at organisations including Cognisco, LLamasoft and Occam DM

Course Structure

Modules

First semester

• Fundamentals of Business

Intelligence Systems

• Data Warehouse Design and OLAP

• Research Methods

• Statistics

Second semester

• Data Mining

• Business Intelligence Systems

Application and Development

• Analytics Programming

Plus two from the following list:

• Management of Information Systems

• Human Factors in Systems Design

• Applied Computational Intelligence

• Artificial Neural Networks

Third semester

• Final Project

Teaching and Assessment

Teaching will normally be delivered through formal lectures, informal seminars, tutorials, workshops, discussions and e-learning packages. Assessment will usually be carried out through a combination of individual and group work, presentations, reports, projects and exams.

Compulsory taught modules give you the opportunity to gain the fundamental knowledge and practices required to apply, develop and research business intelligence systems, while optional modules provide you with chances to study particular aspects of system application and development in more depth.

The individual project module allows you to undertake research into an aspect of business intelligence systems that interests you, and/or to perform appropriate business intelligence development tasks in response to a given practical problem.

Contact and learning hours

Full-time students will normally attend around 16 hours of timetabled taught sessions per week, and can expect to undertake around 24 further hours of self-directed independent study and research to support your assignments and dissertation.

Industry Association

This course was developed and is run in conjunction with SAS. SAS is the world's largest independent business analytics company. It provides an integrated set of software products and services to more than 45,000 customer sites in 118 countries. Across the globe, both the public and private sector use SAS software to assist in their efforts to compete and excel in a climate of unprecedented economic uncertainty and globalization.

To find out more

To learn more about this course and DMU, visit our website:

Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

Applying for a postgraduate course:

http://www.dmu.ac.uk/study/postgraduate-study/entry-criteria-and-how-to-apply/entry-criteria-and-how-to-apply.aspx

Funding for postgraduate students:

http://www.dmu.ac.uk/study/postgraduate-study/postgraduate-funding-2017-18/postgraduate-funding-2017-18.aspx

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IN BRIEF:

• Study a course that is unique in the UK and has been specifically developed to meet the skills gap. Course content can be applied to very diverse fields- there are many job opportunities in this area.
• Gain SAS certification.
• Learn to tell a story from data. Become immersed in Big Data techniques and platforms, working with real-world messy data to gain experience across the data science stack.
• Part-time study option
• International students can apply

COURSE SUMMARY

Have you ever wanted to ‘Mung’ data? Apply Machine Learning techniques? Search for hidden patterns? Be part of Big Data?      

This course is your opportunity to specialize as a Data Scientist, one of the most in demand roles across all sectors including health, retail, and energy. Companies such as Google and Microsoft, and also public organisations such as the NHS are struggling to fill their vacancies in this field due to    a  lack of suitably qualified people. This course is unique in the UK in that it has been developed as a MSc conversion course – if you have a good honours degree in any discipline with a demonstrable mathematical aptitude, an enquiring mind, a practical and analytical approach to problem solving,    and  an ambition for a career in data science; then this course is for you.    

During your time with us, you will develop an awareness of the latest developments in the fields of Data Science and Big Data including advanced databases, data mining and big data tools such as Hadoop. You will also gain substantial knowledge and skills with the SAS business intelligence software suite  due  to    the  partnership of the University with the SAS Student Academy.  

"We are especially pleased to endorse the new MSc in Data Science. With the explosion of interest and investment in data science teams, our customers cannot get enough graduates with SAS-based analytical skills. Courses such as this new MSc are an important step forward by the University to addressing this skills shortage, especially amongst home students." - SAS

COURSE DETAILS

This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project worth 60 credits. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and could lead to ideas that you can develop for your MSc Project.

TEACHING

The course is focused around the underpinning knowledge and practical skills needed for employment within the data sciences industry. There will be 22 hours of lectures; 11 hours of tutorials and 22 hours workshops; 2 hours of examination-based assessment; and 245 hours of independent study, assessed coursework and preparation for examination. This makes a total of 300 hours total learning experience.

• Lectures will be used to introduce ideas, and to stimulate group discussions.
• Tutorials will be used to develop problem solving strategies and to provide practice and feedback with scenarios to help with exam preparation.
• Workshops will be used to develop expertise in SAS tools, by analysing example datasets of increasing complexity.

ASSESSMENT

• 50% of the assessment will comprise a practical project where students will be given some data, will devise and carry out an analysis strategy and will present their interpretations and explain their strategy. 
• 50% will comprise an examination, which will assess more theoretical aspects of the course and will explore students’ immediate response to unseen scenarios or data.

CAREER PROSPECTS

A recent report by e-Skills and SAS (Big Data Analytics: An assessment of the demand for labour and skills, 2012-1017) indicates the demand forecast for staff with big data skills is predicted to ”rise by 92% between 2012 and 2017, and by 2017 there will be at least 28,000 job openings for big data staff in the UK each year…”

With this qualification, you’ll be equipped with the skill set and technical knowledge relevant for the data science and big data job market.

FURTHER STUDY

The Informatics Research Centre in the School of Computing, Science and Engineering at the University of Salford builds on the history, success and achievements of the research in Computer Science and Information Systems developed at the University of Salford over the last thirty years.

Evolving around Data and Information in all their types and usages, the Centre covers all phases and processes from data pre-processing to engineering and visualisation. The Centre is developing novel methods and systems for the analysis and recognition of various data sets, learning behaviours and causal models. The techniques and systems developed have a wide range of potential applications including digitisation of historical documents, medical diagnosis, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval and data visualisation.

Forensic computing, digital investigation and Cyber security is another area of expertise supported by the centre both at the theoretical and application levels.

Many students go on to further research in the fields of:

• Actionable Knowledge Discovery and Semantic Web
• Software Engineering and applications
• Big Data, Data Mining and Analytics
• Image and document processing and analysis
• Cyber Security and Forensics
• Information visualisation and virtual environments

FACILITIES

Facilities include a new Dell Cloud Computing platform with OpenStack and lab workstations, providing access to software platforms and languages specialized in Machine Learning, Data Mining, Statistical Analysis and Big Data including:

• R, SAS Enterprise Guide & Miner, Python, Apache Hadoop & Spark, RapidMiner
• NoSQL databases ie MongoDB

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Learn how to overcome the major challenges facing industry, business and the public sector today, and influence the decision-making processes of the future.

• Gain a solid theoretical foundation and quantitative skills, alongside practical problem-solving techniques
• Apply your knowledge to real-life scenarios using case studies, individual and team consulting-based assignments, presentations and software tools
• Use SAS Enterprise as part of the `Data Analytics for Business Decision Making' unit. SAS sponsor a coursework prize for this project
• Choose from a broad range of options to meet your interests or career aspirations
• Prepare for a career in consultancy, finance, retail, manufacturing, government analytics units, defence, IT systems, outsourcing and telecoms.

Special features

We run a core module on Data Analytics which will introduce students to SAS Enterprise. A coursework prize for this project will be sponsored by SAS.

Recent highlights included a case study run by British Airways, a presentation from SAS on the Future of Analytics and ongoing dissertation projects with Unilever and LBM.

Coursework and assessment

Assessment varies depending on course units taken. It may include a combination of course work, group project assessment and presentations, report, assignments, in-class tests and examination. The dissertation normally ranges between 12,000 and 25,000 words.

Course unit details

During the course you will be taking 180 credits in all. The eight taught modules during semester one and two total 120 credits and consists of both compulsory and optional taught units which can be viewed in the list below.  

The core courses unit introduce you to mathematical principles and practical tools for Optimization, Decision Making, Data-Mining, Statistical Analysis, Simulation and Risk Analysis. Specific software packages include SAS, SPSS, Minitab, AMOS, Eviews, Excel, Excel Solver, SIMUL8, iThink, Risk Solver, IDS.

Over the summer period, you will carry out your Research Dissertation, worth 60 credits. Examples of recent dissertation project topics include:

• Web analytics for evaluating online user experience
• Capacity management of product test equipment
• Risk management in the hotel industry 
• Equity forecasting using ARIMA and neural networks
• Predictive modelling: A case study for selling additional contracts to existing customers in the telecommunications industry

Scholarships and bursaries

Contact us for further information on scholarships available .

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]

Career opportunities

There are many potential career roles for postgraduates with an understanding of analytical approaches in business and management - including job titles such as operational research analyst, systems analyst, risk analyst, financial analyst, performance analyst, business analyst, marketing analyst, business modeller, and operations, logistics, production, project, risk, quality, performance, or general manager. Employers include general and specialist consultancies, the finance, retail and manufacturing sectors, government analytics units, defence and major 'solution providers' in IT systems, outsourcing and telecoms.

In many of these areas an MSc is generally accepted as highly desirable for developing an initial career in the field. In addition to preparing you for specialist professional work, the course is also a valuable preparation for further study and for research degrees.

More details on our Careers Service.

Latest information on visa changes and opportunities in the UK for international students.

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Developed to meet the demand for data science professionals, our postgraduate Data Analytics course enables you to effectively structure, analyse and gain insight from a wide range of complex data across different industries.

Designed in close consultation with industry partners including the NHS Business Services Authority, Teradata, BT, SAS, the Pensions Regulator and local Brighton companies, your learning is informed by current business developments through case studies looking at real-world data sets, research questions and scenarios. You have the opportunity to collaborate on projects with our industry partners, and can also use your own data, project ideas and industry links.

Guest lecturers will share their knowledge and expertise with you, such as Tom Khabaza who is a founding chairman of the Society of Data Miners, author of 9 Laws of Data Mining and was involved in designing the course.

You will develop a skill set in specialist data analytics and associated software, quantitative methods and techniques, and business intelligence. Our staff are experts in their field and you have the chance to develop your knowledge in specialist areas where we have ongoing research and expertise, such as sequential forecasting, natural language processing and image processing.

Whether you are a recent graduate or an experienced professional wanting to gain data analysis skills, this course is available on a full or part-time basis to help you manage your studies around other commitments. 

Course structure

The course covers three main areas:

• data management – structuring and manipulating data for analysis purposes
• data interpretation – statistical analysis using advanced features of industry-standard software such as SAS, SPSS and R
• project management – the business-specific and strategic aspects of analytics.

You will learn how to assess project viability, propose sound business cases and strategies for analysis, perform and oversee analysis and manage large data projects successfully as well as developing your critical appraisal and presenting techniques. 

Based at our Moulsecoomb campus, you will have access to computer and research labs equipped with specialist, sophisticated software including SAS, SPSS Statistics and SPSS Modeller. Affordable student licences for home use are also available. 

With a flexible timetable to suit full-time or part-time students and commuters, and lecturers available to support you in your module choices, there are different study routes available to you.

Syllabus

You will study five core modules. One of these involves a major project, potentially in collaboration with industry. You will also choose option modules, subject to availability, allowing you to focus on particular areas of interest.

Core modules

• Data Management – provides an understanding of contemporary database management systems. Explores a methodology for database design and development, and develops skills in searching, reporting and analysing the data. Topics covered include database implementation and administration, data modelling and business intelligence.
• Programming for Analytics – provides competencies in computer programming and algorithm design with emphasis on statistical programming and data analysis. The module covers both general issues of algorithm design and data structures and implementation issues in R and SAS.
• Data Visualisation and Analysis – covers principles of data visualisation and specialised tools for data visualisation and analysis such as SAS Visual Analytics and Qlikview. The module also explores the mathematical and statistical theory behind data analysis.
• Business Analytics Strategy and Practice – develops analytics-specific project planning concepts within this context, enabling students to design and manage analytics projects and present the business case to senior management.
• Industry project – substantial, independent project undertaken with the supervision of a member of the teaching team. Projects are normally industry-based using real data sets.

Option modules*

• Multivariate Analysis and Statistical Modelling – design statistical experiments, analyse multivariate data and apply classical and modern statistical modelling techniques. Enhances skills in the use of specialist software such as R, SPSS or SAS.
• Data Mining and Knowledge Discovery in Data – find useful and relevant patterns, trends and anomalies in data sets, and summarise them in a form which may be used to support enterprise decisions – one of the great challenges of the information age. Emphasis is on the big, real-world picture rather than inside-the-box systems design engineering details. 
• Stochastic Methods and Forecasting – an understanding of stochastic models and their applications in a business context. The module also covers forecasting methods with the emphasis on selecting the best forecasting method for a business problem and correct application of that method.
• Risk Analysis and Retail Finance – introduction to the statistical methods used to estimate risk and reward in retail credit. The focus is on retail finance especially the provision of credit and lending services.
• Medical Statistics – introduction to the methods originally designed for clinical trials and now being used in other contexts including sociology and marketing research. Topics include assessment of risk factors, comparing treatments and assessing survival data.

*Option modules are indicative and may change, depending on timetabling and staff availability.  

Employability

A wide variety of organisations draw upon data analytics specialists to help produce valuable information for decision-making, for example commodity price forecasting, customer intelligence, clinical trials, R&D and many other areas utilising large amounts of data.

Graduates are able to choose from a range of private, governmental and academic roles, depending on their personal interests. Some of our full-time students find a full-time job and switch to part-time study in the middle of the course.

Graduate destinations include:

• government bodies such as the Pensions Regulator and local councils
• transnational corporations such as Capgemini
• local companies such as iCrossing.

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Big data is the description used to encompass the huge amounts of data that is common to many businesses. It has been described as the next frontier for innovation, competition and productivity in business. It is essential for companies to embrace so that they can understand their customers better, develop new products and cut operational costs.

This course has been developed to create graduates who can become data scientists capable of working with the massive amounts of data now common to many businesses. It is aimed at people who want to move into this rapidly expanding and exciting area.

The modules on this course help you develop the core skills and expertise needed by the data scientist. The course can be split into three main areas, statistics, computing and management.

In the statistics section you study modules on data mining and data modelling. These modules cover the three main data areas, which are ensuring that data is reliable and of a high quality, searching the data to discover new information and presenting interpretations of that data to the end user.

The computing section covers areas related to data integration, massive datasets stored in the cloud, how data is stored and utilised within the distributed systems of an enterprise and how organisations can utilise data to change and improve business processes.

The management modules are focused on developing your core skills around professionalism and research. All of which are valuable skills during your university studies and in your career.

Our partnerships with business inform the course design, ensuring the content is relevant, up to date and meets the needs of industry. These partnerships also enable the inclusion of some leading edge software such as SAS, SAP Hana, and Hadroop within the course. You may be able to study abroad as part of the Erasmus programme.

Key areas of study

Key areas of study include • data quality and analysis • technologies to store and mine data • professionalism and research

Professional recognition

This course includes the SAP Business Intelligence with SAP BW 7.3 and SAP BI 4.0 e-academy (UB130e). You also have the opportunity to sit the SAP certification exam and the SAS 9 base certification exam.

Sheffield Hallam is a member of the SAS Student Academy, the SAP Student Academy and founding member of the SAP University Alliance.

Course structure

Full time – September start – typically 12 or 18 months

Part time – September start – typically 36 months

Core modules

• research skills and principles
• industrial expertise
• data integration
• statistical modelling
• data mining
• handling data in the cloud
• big data and distributed systems
• social and economic aspects of the cloud
• advanced statistical modelling
• dissertation

Options

Choose one from :

• organisational dynamics
• social and economic aspects of the cloud

Assessment

• essays
• assignments
• computer-based tests
• practical projects
• presentations
• vivas

Employability

Many jobs for data scientists, data analysts and data mining analysts are available with salaries ranging from £35,000 to £80,000.

Jobs typically list the skills to be in areas such as statistical analysis and machine learning techniques, database and programming technologies, and expertise in statistical theory, which are all areas you cover on this course.

You also gain skills and knowledge in HaDoop, MapReduce, Java, SAS, MSQL which are some of the common technologies used in data scientist roles.

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Our MSc in Big Data Analytics provides a foundation for you to pursue a career applying leading edge software analytics technology or conducting research in this vitally important field. It will give you in-depth knowledge and critical understanding of the key issues and concepts. You’ll develop powerful skills in the extraction, analysis and management of information from big data using a variety of scientific techniques and software tools.

One of the course’s key strengths is that it is designed in conjunction with SAS, the global leaders in data analytics, whose data mining and business intelligence platform is widely used in academia and industry. You’ll have the opportunity to gain SAS 9 base certification. We also boast strong links with employers through our research and high profile consultancy projects, ensuring that our teaching remains up-to-date and relevant.

You’ll be introduced to knowledge discovery, analysis and assessment of data extracted from structured and unstructured big datasets, visualisation and communication of results. You’ll process advanced knowledge and information, make deductions and form
conclusions. The practical skills you’ll develop include computer modelling and the design and analysis of big data sets. The broader
skills include communication, teamwork, management and the ability to use advanced quantitative methods.

As part of your studies, you’ll address real-world industry-based problems during supervised computer sessions and through independent work. This intellectually demanding process requires not only specialist knowledge of big data analytics, but also the ability to apply multidisciplinary concepts to today’s dynamic business and scientific areas.

With the MSc, you’ll be equipped for careers in business intelligence and data analytics in any type of industry, in consultancy or in entrepreneurship. The course also provides a foundation for progression to a PhD or MPhil, allowing you to pursue your research interests.

You’ll study modules such as:

Business Analytics with SAS
Statistical Techniques
Studying at Masters Level and Research Methods
Processing Big Data
Information Visualisation
Analytics: Ethics, Trusts and Governance
Comparative Analytics Tools
Natural Language Processing
Optimisation
Independent Scholarship

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This postgraduate Masters course is uniquely designed for both computing and non-computing graduates wishing to pursue a career in data science community.

Data science is at the intersection of the fields of computer science, statistics, and design. In a rapidly evolving world, new types of big data are emerging from mobile devices, sensors, instruments, transactional systems, web logs, social media, the cloud and other sources. Businesses are accumulating big data at a rate that often exceeds their capacity to extract value from it.

MSc Data Science is ideally placed to provide you with technical knowledge and employer-focused skills required in a data scientist role. The course will develop your specialist knowledge of data acquisition, data cleansing, data analysis, information extraction, prediction, visualization, story-telling and explanation.

You'll gain hands-on experience using industry standard tools for data science, business intelligence and analytics including SAS, Tableau MS SQL Server, Oracle Database, and R Programming.

Modules

Research methods and professional issues
Future internet technologies
Statistical analysis and modelling
Business intelligence
Data management
Machine learning
Data mining and analysis
MSc thesis

All modules are assessed by a mix of coursework and examinations.

Teaching and learning

You'll make use of our e-learning suite and learn in a combination of lectures, seminars, workshops and private study. You'll have access to specialist software including Microsoft SQL Server 2012, Netbeans 7.x with Java 7, Oracle, Python, SAS and Visual Paradigm.

Placements

You are encouraged to actively seek placements, work experience and voluntary work during your studies to improve your CV and to give you the opportunity to put theory into practice. Many opportunities are offered through the University's central Employability team, who can support you in finding a placement.

Accreditation

In order to ensure the course runs in accordance with industry recognised standards we are seeking accreditation for both Chartered Engineer (CEng) status as well as Chartered IT Professional (CITP) accreditation by the British Computer Society, the Chartered Institute for Information Technology.

We are also seeking Chartered Engineer (CEng) status with both the Institute of Engineering and Technology and the Engineering Council.

Employability

Career opportunities range from IT services to business consultancy, and this course will prepare you for a career in the business intelligence community working actively with a range of resources including tools from major commercial vendors such as Microsoft and SAS.

As a graduate of this course you should to be able to work within the areas of business intelligence or business and data analytics, in roles such as a business intelligence specialist, data or business analyst or business intelligence developer.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

• Direct engagement from employers who come in to interview and talk to students
• Job Shop and on-campus recruitment agencies to help your job search
• Mentoring and work shadowing schemes.

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Centennial College's Marketing Research and Analytics program positions you at the forefront of a cutting edge job market in which organizations have oceans of data available to them but struggle to make sense of it as marketing becomes increasingly data-driven. As a result, there is a large and growing demand for trained researchers who can harness the power of big data using the latest tools and analytical techniques to uncover new insights and drive businesses forward.

This Marketing Research and Analytics program combines advanced courses in marketing research and big data analytics with training on leading commercial technologies and platforms and the opportunity to gain in-demand industry certifications.

This program equips you with knowledge, skills and training in leading business intelligence and marketing research technologies and tools used in the field. Among them are SAS Enterprise Guide and SAS Enterprise Miner, Environics Analytics Envision (used to develop comprehensive profiles of selected target markets), SPSS, Tableau (the leading data visualization software), Excel, XL Miner, Dell Factiva and NVIVO (qualitative research and text analysis software).

Upon graduation, you receive an Ontario Graduate Certificate from Centennial College, plus certificates of recognition from SAS and Environics Canada. In addition, you are put on an accelerated track to earning the Certified Marketing Research Professional (CMRP) designation, the premier credential in Canadian marketing research from the Marketing Research and Intelligence Association (MRIA).

Career Opportunities

Program Highlights
-The Marketing – Research and Analytics program combines marketing research principles and skills with cutting edge "big data" analytics techniques to equip you with the training required to deliver insights and strategies to help organizations make smarter and more impactful business decisions.
-Employed is an extensive use of learner-centered approaches such as case studies, simulations and project-based learning, with a focus on developing project management, teamwork, analytical thinking, and report writing and presentation skills.
-Hands-on learning covers areas such as questionnaire design, data manipulation, quality control, statistical output and program development.
-There is a strong focus on applying marketing research and analytics to strategic marketing decision-making.
-In the second semester, you develop and implement a capstone project that will integrate and apply your learning.
-In addition to market research technologies, you also have access to the full suite of Microsoft products, including Microsoft Excel, XL Miner, Access and PowerPoint.
-Once you graduate, you have the option to take the Comprehensive Marketing Research Exam (CMRE) on campus at Centennial College, which leads to the Certified Marketing Research Professional (CMRP) designation.

Articulation Agreements
Start with a graduate certificate, and continue to a master of business administration through our degree completion partnership. Successful graduates of this Marketing – Research and Analytics program may choose to continue with courses leading to a graduate degree.

Career Outlook
-Marketing research specialist or analyst
-Research analyst
-Marketing research and intelligence coordinator
-Market intelligence specialist or analyst
-Customer insights analyst
-Consumer research manager
-Business intelligence analyst
-Market research analytics manager
-Web marketing analyst
-Customer experience analyst
-CRM analyst
-Direct response analyst
-Digital marketing analyst
-Social media analyst
-Data and analytics specialist
-Business analytics specialist
-Loyalty program analyst
-Sales analyst
-Marketing strategy analyst

Program Outcomes
-Optimize the financial results produced by interactive marketing programs through the application of marketing analytics
-Contribute to the design of a marketing analytics team project (develop charter, business case financials, technical requirements, design, test plan, test results, approval to proceed) and the management of the resulting project
-Create, manage and mine, and apply modelling and decision making functions to a database
-Utilize data auditing techniques and quality control processes that are consistent with current marketing research codes of conduct and Canadian privacy principles to ensure the integrity of the data collection, storage, analysis and presentation processes
-Compare and contrast, evaluate and select appropriate data sources to meet specific marketing objectives
-Conduct industry, competitor and customer analyses using a wide variety of secondary research sources
-Produce reliable and analyzable data through the application of sound questionnaire design principles to marketing research projects
-Design marketing research projects and interactive marketing programs that are founded in sound sampling techniques, hypothesis testing and research design
-Solve business and marketing problems by identifying, selecting and applying effective, current and relevant techniques such as descriptive and inferential analysis
-Prepare provisional output of analyses including cross-tabulations and pivot tables that address the needs of analysts and prepare final output, including research reports, presentation sides and visual representations of data that address the needs of management
-Develop actionable recommendations based on situation analyses and research findings

Areas of Employment
-Retail corporations
-Organizations with in-house analytical and research functions
-Marketing research firms

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STATE-OF-THE-ART RESEARCH IN METHODOLOGY AND STATISTICS

Modern society is highly data-driven. Everything is monitored and measured, yet there are major challenges to finding optimal ways to design research, analyse data, and extract the most valuable information.

This selective Master’s programme combines the research expertise of the following departments at Utrecht University (UU) and the University of Twente (UT):

• Department of Methodology and Statistics (UU)
• Department of Biostatistics, University Medical Centre Utrecht (UU)
• Department of Research Methodology, Measurement and Data Analysis (UT)

This programme therefore also has two main study locations you can choose from, that is, either Utrecht University or the University of Twente. The collaboration between these departments provides you with an exceptionally broad range of internship opportunities and thesis topics focused on the following fields: Behavioural Sciences | Biomedical Sciences | Social Sciences

HIGH QUALITY

The programme is recognised as a high quality programme and has been awarded high ratings in the past years by established rankings in the Netherlands. 

COMBINING THEORY AND APPLICATION

Through the programme’s cutting-edge research in methodology and statistics, you will acquire the knowledge and skills needed to carry out fundamental and applied research at the level of a PhD project. This two-year Master’s programme provides you with answers to questions such as:

• What is the best way to set up a clinical trial to test new medical treatments?
• How do we estimate the number of illegal immigrants in the Netherlands?
• How do we obtain valid answers in a survey about sensitive topics like income or tax fraud?
• How do we accumulate knowledge through Bayesian updating techniques?

You will also develop your ability to consult with applied researchers on a wide range of methodological and statistical issues. During your studies, you will select a specialisation in the behavioural, biomedical, or social sciences, which you will explore in depth through electives and (the preparation for) your Master’s thesis.

INTERNATIONAL ORIENTATION

Every year, students are invited to participate in the organisation of conferences, through which they have the opportunity to interact with scientists from around the world. In addition, there are opportunities to take electives abroad.

EXCELLENT CAREER PROSPECTS

The Methodology and Statistics programme prepares you for a scientific career in academia, research institutes, government organisations, NGOs, or private enterprises. Utrecht University, University Medical Centre Utrecht, and the University of Twente maintain strong partnerships with various non-academic institutions, such as CITO, CentERData, CBS, TNO, UMCU, LSAC, CTB, ETS, AMC, SAS, Ministry of Education, Ministry of Social Affairs and Employment, Stichting Arq, Dutch Inspectorate of Education, Danone, and Ex:plain, which provide excellent career prospects for our students. The majority of our graduates obtain positions as PhD students either in one of the three departments that coordinate this Master’s programme or in other related departments in the Netherlands or abroad.

THESIS AND PREPARATION

You can prepare for and write your thesis at one of the three participating departments, or you can broaden your experience by working with other organisations, such as Statistics Netherlands, CITO, Social Cultural Planning Office, TNO, Research Centre for Examination and Certification, or UMCU.

PROGRAMME OBJECTIVE

Through this Master’s programme, you will develop the skills and knowledge to function as a qualified practitioner who is ready for PhD training or a research career outside academia. You'll learn how to:

• develop methodological and statistical approaches that are required by new developments;
• evaluate commonly used methodological and statistical approaches; and
• apply methodological and statistical approaches in cooperation with behavioural, biomedical, and social sciences researchers.

You will be fully equipped with the academic skills and knowledge necessary for your future career.

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This programme is for future leaders in logistics management, supply chain management, operations management or purchasing, whatever career stage they are at.

The course is accredited by the Chartered Institute of Logistics and Transport (CILT). Strongly practical in focus, this MSc will equip you with a formidable set of analytical, technical, creative and collaborative skills; vital for your future professional career. The programme takes in both traditional and digital-age manufacturing as well as service industries and is, therefore, relevant to a wide range of organisations. During the course there are opportunities to gain practical experience and use industry-leading tools such as SAP and SAS.

Our strong connections to industry and government ensure that your learning has a highly practical focus, both in teaching and in the three-month live business dissertation project. Our lecturing team consists of practitioners as well as academics. The programme includes guest lecturers from industry to enhance the experience and provide you with the opportunity to interact with real-life businesses. For those seeking a global career, this programme provides a fantastic opportunity.

Course Structure

You will study a range of modules as part of your course, some examples of which are listed below.

Core

• Problem Solving Skills for Consultants
• Global Sourcing and Business Services
• Logistics Modelling
• Spreadsheet Modelling
• Operations and Supply Excellence
• Applying Statistical Models in Business
• Strategic Supply Chain Management
• Masters Research Project
• Masters Research Dissertation

Optional

• Data Mining for Marketing, Sales and Finance
• Business Analysis and Enterprise Systems
• Problem Structuring
• Computer Simulation
• SAS Programming for Business Analytics
• Stochastic Modelling
• Optimisation and Heuristics
• Marketing Research Methods
• Forecasting
• Marketing Analytics and Modelling
• Introduction to Python Programming

Information contained on the website with respect to modules is correct at the time of publication, but changes may be necessary, for example as a result of student feedback, Professional Statutory and Regulatory Bodies' (PSRB) requirements, staff changes, and new research.

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Learn how to gain insights and understanding from large data sets by using statistical methods, and how to apply these to business problems. Through this MSc, you’ll develop an understanding of the role of an analyst within an organisation, improve your business acumen and communication skills, and get commercial/research experience for your CV through your project and dissertation.

Course details

You will study four compulsory modules to give you an overview of key business areas, and take four optional modules of your choice available through various study routes on this one-year course. Please note that availability and delivery modes may vary. Assessment is usually a mix of exams and coursework. Your project and dissertation will either be as a consultant to an organisation or as applied research.

Programming skills

We support the learning of multiple programming languages with access to a variety of interactive online materials, covering SAS programming (provided by the SAS Institute), R and Python (provided by Data Camp). 

Consultancy project

Working as a consultant tests your ability to assess a problem and adopt the best approach to tackling it, as well as your client liaison and management skills. You will usually write a client report in addition to your 12,000 word dissertation.

• Review & development of pricing models for a leading bank
• Market strategy for a manufacturing group
• Developing a bespoke analytical tool for a leading internet provider
• Identifying benchmarking guidelines for the service operations industry

Research project

A research project allows you to explore a topic critical to effective decision-making in organisations. Supervised by one of our academics, demonstrate you can undertake systematic and rigorous applied research over 12,000 words.

Previous research projects

• The impact of analytic consulting interventions
• Rational consumer behaviour & decision-making
• The impact of the EU Emissions Trading Scheme on reducing CO2emissions
• An analysis into the effects of advertising and word-of-mouth

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This programme is ideal if you wish to use your analytic skills to derive and obtain useful insights from large amounts of data. By equipping you with the rigorous modelling and consulting skills needed to understand, manage and communicate useful insights from ‘big data’, it prepares you to inform business decisions or government policies.

Taught modules are delivered by our group of internationally recognised management scientists who are actively working with business, government and non-profit organisations to tackle routine, strategic or policy problems.

Our industry advisory board ensures that the focus of our taught modules is of both academic and practical relevance. IBM, our partner, has jointly developed with us two modules (Customer Analytics and Leading Analytics Initiatives), and sponsors a student prize.

During the summer, you will undertake a supervised consulting or research project. This will give you the opportunity to apply powerful tools such as data mining, forecasting, optimisation, simulation and decision analysis to a particular area of business or policy, equipping you with skills highly prized by employers.

Core study areas include consulting for analytics, discovery analytics, decision analytics, managing big data, customer analytics, leading analytics initiatives, operations analytics, policy and strategy analytics, and a consulting or research project.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/business-analytics-consulting/

Programme modules

Semester 1:
- Consulting for Analytics
You will learn the craft and skills required by analytic consultants, and which employers look for but often find lacking. It will cover process aspects of analytics projects, as well as skills in client interaction, problem structuring and data elicitation (with individuals and/or groups, and with hard/soft data), presenting data-driven analyses, report writing, and developing simple bespoke decision support systems.

- Discovery Analytics
You will be introduced to common statistical methods to explore and visualise cross sectional and temporal data. You will also learn about the design and conduct of data collection efforts, together with methods for dealing with data outliers and missing data. Industry-leading tools that are in high demand from employers (e.g. SAS and SPSS) will be used.

- Decision Analytics
Your will be introduced to common operational research techniques to help determine the best course of action for a given decision or problem. Topics covered include optimisation, simulation and decision and risk analysis.

- Managing Big Data
Your will learn about the challenges and opportunities derived from the increased volume, variety, velocity and value of data that is available today. A range of big data topics will be covered including data type, data integration, data technologies, and data security.

Semester 2:
- Customer Analytics
You will focus on analytics techniques that can help organisations gain a deeper insight into customers’ behaviour and attitudes towards their products and services. It will cover approaches designed to provide a profile of customer segments, such as those grounded in data mining and multivariate statistical analysis. Industry-leading tools that are in high demand from employers (e.g. SAS and SPSS) will be used. There is an IBM sponsored student prize on this module.

- Leading Analytics Initiatives
You will learn about the issues associated with implementing an analytics capability in organisations. It will cover topics on how to develop an analytics strategy, how to embed analytics in organisational processes to ensure they deliver value, and how to deploy analytics throughout the organisation to improve decision making. There is an IBM sponsored student prize on this module.

- Operations Analytics
You will focus on analytics techniques that can help organisations to develop a better understanding of operational processes, and identify efficiency and cost reduction opportunities. Topics covered include advanced optimisation and simulation techniques.

- Policy and Strategy Analytics
You will focus on analytics techniques designed to tackle complex policy and strategic issues. It will cover approaches designed to explain the behaviour of complex social systems or assess the consequences of complex decisions, in order to provide the levers for policy and strategy making in a variety of sectors.

Summer:
- Consulting or Research Project

Assessment

Taught modules are assessed by a mixture of coursework and examinations.
The summer project is assessed via a written dissertation.

Careers and further study

Business analytics is a new and rapidly developing field, and individuals with analytics skills are in short supply.
Graduates from this programme can expect to work as management consultants, business analysts, policy analysts, marketing researchers, operations researchers, and data scientists.
We have developed two modules - Customer Analytics and Leading Analytics Initiatives - in close collaboration with our partner IBM, who also sponsor a student prize.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/business-analytics-consulting/

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