Course Overview

Attendance
UK/EU Fees £1,075 *
International Fees £1,500 *
Alumni Discount See details
Duration 2 years

* Price per 20-credit module

Course summary

This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Course structure

The following modules are indicative of what you will study on this course.

Core modules

The module discusses how to manage the volume, velocity and variety of Big Data, SQL and noSQL databases, and it touches on issues related to data governance and data quality.

This is a self–contained module in applied statistics and operational research (OR) for decision making that lays the foundations for more advanced modules in data mining, optimisation and simulation modelling. It covers the essential of descriptive, predictive, and prescriptive analytics in an application driven manner and makes use of appropriate software tools such as EXCEL and R to derive meaningful solutions.

This module will provide an overview of modern techniques in Machine Learning and Data Mining that are particularly customised for Data Science applications. Students will work with select data sets, related to the specific public sector or businesses application domains. Students will work through exercises that provide opportunities to explore the features and strengths of different machine learning and data mining methodologies. A range of toolkits will be introduced, such as R and Python.

The module strengthens student’s skills for the research and industry needs in the area of their studies, their final project, and their professional development. It guides the students’ personal development plan towards the professional requirements of the discipline, and covers methods of critical evaluation, gathering and analysing information, and preparing and planning a project proposal.

The project module plays a unifying role and it aims to encourage and reward individual inventiveness and application of effort. The scope of the project is not only to complete a well-defined piece of work in a professional manner, but also to place the work into the context of the current state of the art in business intelligence and/or analytics.

Option modules

The module teaches students how to use Big Data Analytics in enterprises considering both the latest research achievements and technology trends. It gives an overview of the underlying concepts and technologies of Big Data Analytics, such as Hadoop, MapReduce, Hive, etc. It covers the whole data lifecycle from creating to processing data and from publishing and to preserving data.

The module provides an in-depth analysis of advanced topics in operational research such as discrete optimisation, multiple criteria optimisation and modern heuristic approaches.

This module covers the theoretical and practical aspects of data visualisation including graphical perception, dynamic dashboard visualisations, and static data ‘infographics’. Tools such as R and Tableau are used. The aim is to prepare students for becoming a data visualisation specialist.

This module teaches students how to build Data Warehouses by understanding their structures and the concept of multi-dimensional modelling. The focus is on Data Warehouse design, multi-dimensional modelling, the integration of multi-source data and analysis, cloud-based data warehousing, NOSQL OLAP, aiming to support better business decision making.

An introductory module that covers theoretical & practical issues related to technologies employed in persistent storage of data. It evaluates underlying technologies & approaches used in capturing, maintaining & modelling persistent data; reviews the evolution of DBMSs their components & functionality, along with some of the predominant & emerging data models; addresses practical issues related to conceptual data modelling, practical & current trends in database design; it also discusses in detail the features and constructs of the SQL, the de-facto database language for the definition and manipulation of relational data constructs.

The module focuses on the choice and use of appropriate simulation modelling approaches to treat real–world problems, developing solution(s) using powerful simulation software and explaining the business and industrial implications thereof. Relevant applications to problems such as stock control, reliability, project management, and service redesign will be considered in domains such as healthcare, supply-chain, and transport.

This module explores the use of modelling to analyse and measure both online presence and impact using web and social media data. During the module students will learn how to listen to social media conversations taking place and how such data can be transformed into actionable insight for a brand or organisation. Furthermore, we will study ways in which the effectiveness of modern websites are often judged and how online web metrics can be used to drive performance. The overriding aim of the module is to equip students with the necessary technical skills and industrial knowledge for a career in the area of web or social media marketing.

You may take instead another postgraduate module in the Department, at the course leader’s discretion.

Professional recognition

This course is accredited by the British Computer society for partial fulfilment of the academic requirement for Chartered IT professional.

Entry Requirements

You are expected to already have quantitative skills, with an interest in developing these further to support postgraduate activity in analysing, evaluating and reporting on a range of real-world data-intensive problems. You will have a suitable Honours degree from a UK university (or equivalent qualification) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course. 

If your first language is not English, you will need an IELTS score of 6.5 or equivalent.

View more information about our entry requirements and the application process

 

 

You are expected to already have quantitative skills, with an interest in developing these further to support postgraduate activity in analysing, evaluating and reporting on a range of real-world data-intensive problems. You will have a suitable Honours degree from a UK university (or equivalent qualification) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course. 

If your first language is not English, you will need an IELTS score of 6.5 or equivalent.

More information

Careers

Our Career Development Centre has just been shortlisted for the Best University Careers Service in the National Undergraduate Employability Awards for 2017.

With a growing network of over 3,000 employers around the world and a team of experienced careers consultants, we are here to help you succeed.

In 2015–16, we helped over 1,500 students find work placements across a range of sectors, with 250 employers attending 14 on-campus skills and careers fairs.

As a Westminster student, you’ll have access to our services throughout your studies and after you graduate.

We can help you:

  • find work placements related to your course
  • find part-time/vacation, placement and graduate jobs, including voluntary experience
  • find international opportunities to enhance your employability
  • market yourself effectively to employers
  • write better CVs and application forms
  • develop your interview and enterprise skills
  • plan your career with our careers consultants
  • meet employers and explore your career options at our employer fairs, careers presentations and networking events throughout the year

Find out more about the Career Development Centre.

Graduates can expect to find employment as consultants, decision modelling or advanced data analysts, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (e.g. GlaxoSmithKline, British Airways, Santander and Unilever), public sector organisations (e.g. the NHS and primary care trusts), retail head offices, the BBC, the Civil Service, and the host of banks, brokers and regulators that make up the City, along with all the specialist support consultancies in IT and market research and forecasting, all of whom use data for the full range of decision making.

Our dedicated Career Development Centre is actively working with an ever-expanding network of over 3,000 employers to provide you with exceptional employability support and guidance. As a result we were nominated as finalists for a significant industry award – the NUE Awards Most Improved Commitment to Employability 2016.

We provide our students with work placements and international opportunities to support them in becoming highly employable, globally engaged graduates, and with one million businesses operating within 20 miles of the University of Westminster, over 84% of our students are in work or further study six months after graduation. Our graduates work in a variety of sectors and organisations, from small/medium-sized companies and start-ups to large not-for-profit organisations and corporates.

During your time at Westminster you will be able to use our comprehensive online vacancy service and meet with our experienced careers consultants, providing you with thorough training and support on CV writing, application forms, interview preparation and assessment centres.

In addition to this, you will receive careers support from academic staff and faculty work placement teams, offering targeted course-specific careers advice and assistance in securing a work placement during your time at Westminster. You can find out more about course-specific career opportunities by visiting the Prospects website.

For more details, visit the employability section on our site.

Our Work Placement Teams are based in your Faculty Registry Office and can help you find a suitable placement, as well as support you in making applications, writing CVs and improving your interview technique.

More details on work placements can be found on our Work placements page.

What our students say

Miryam Ben-chaim

Business Intelligence and Analytics MSc

I have been approached by numerous companies including MI5 and consulting firms since I added my masters to my CV. I have received a 40% increase in my salary from when I started the course to now, therefore pursuing the masters has had a significant impact to my earning potential and opportunities.

Data Architect, Financial Conduct Authority (Fca)

Colin Ridley

Business Intelligence and Analytics MSc

The course did not just challenge and stretch me, but exposed me to such a variety of tools, concepts and systems that I have walked away, more prepared to face the challenges of an ever changing and complex business world.  In some respects it’s like putting on 3D glasses for the first time and seeing angles, dimensions and views you would never have seen otherwise.

Manager Revenue Optimisation, Emirates

Fees and Funding

UK and EU tuition fee: £1,075 (price per 20-credit module)

Find out how we set our tuition fees.

Alumni discount

This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.

Funding

As well as tuition fee loans, there is a range of funding available to help you fund your studies.

Find out about postgraduate student funding options.

Scholarships

The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible undergraduate students, which cover all or part of your tuition fees.

Find out if you qualify for one of our scholarships.

International tuition fee: £1,500 (price per 20-credit module)

Find out how we set our tuition fees.

Alumni discount

This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.

Funding

Find out about funding for international students.

Scholarships

The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible undergraduate students, which cover all or part of your tuition fees.

Find out if you qualify for one of our scholarships.

Course Location

Find out more

More information

Your Westminster

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