The course has been specifically designed to give a structured understanding of business analytics and the practical tools, which can drive business advantage. We’ll teach you how to analyse business data and solve business problems analytically.
We start by providing an overview of big data and business analytics and its context in a business environment where data is rapidly becoming one of the most valuable assets. We will introduce you to the historical context and growth of big data, as well as the characteristics defining big data. We also encourage you to consider the social, ethical and legal implications of handling, storing and using all manner of datasets.
We then focus on the underpinning analytical techniques and tools used to analyse and interpret data, forecast future trends, automate and streamline decisions and optimise courses of action. This includes statistical analysis, data mining, forecasting and regression, optimisation, simulation and spreadsheet modelling. You should also gain a deeper understanding of the value and benefits of different analytical techniques for advanced decision-making and how they can be used to identify patterns, relationships, associations, factors and clusters.
Finally, we consider how to apply analytical methods and techniques to specific business functions, such as an organisation’s marketing function, value chain and financial planning. For example, we will consider how to assess financial performance and economic conditions of a business, identifying relevant costs for short-term and long-term decision-making.
Why choose this course?
In a competitive global market, businesses need skilled analysts who can not only forecast future results, but also test previous decisions and strategies, explaining why certain results occurred. Such skills are prized in the current knowledge economy.
This new course has been specifically designed to provide a real-world context and develop a structured understanding of business analytics. You can learn to apply descriptive and predictive modelling techniques to help organisations improve performance, explore alternatives and understand business data in a rapidly changing world.
It is aimed at students with an undergraduate degree in business and good numerical skills who want to build quantitative and data mining skills to solve business problems by analysing data and converting that information into a strategic asset.
Using case studies and projects from industry, you will work on industry problems and propose tactically viable recommendations based on your analysis.
You will have opportunities to gain hands-on experience of up-to-date technology including SPSS and NVivo, with access to multiple data resources, including ProQuest, Mintel, Science Direct and Emerald. At the same time, you can improve your business understanding and important communication skills.
Coventry has been educating business professionals for over 100 years. Our teaching staff have significant experience of the business world, and have worked as directors and consultants for many large multinational companies not only in the United Kingdom but also abroad.
Your teaching will be research-informed by staff with an international reputation for research in the areas of international business and management, global supply chain and logistics, business process integration, internationalisation of SMEs, change management and many more. In the most recent national research assessment exercise, the 2014 Research Excellence Framework (REF), 85% of the School’s ‘Business and Management’ research was recognised internationally, of which 13% received the highest ‘world-leading’ classification.
For details about individual modules please visit the course page on our website.
This course will be assessed using a variety of methods which will could vary depending upon the module. Assessment methods include dissertation/management consultancy project, reports, practical coursework, presentations, formal examinations and portfolio.
The Coventry University Group assessment strategy ensures that our courses are fairly assessed and allows us to monitor student progression towards the achieving the intended learning outcomes. Assessments may include exams, individual assignments or group work elements.
Applicants will normally hold a good honours degree in a relevant academic discipline. Applications from candidates with relevant experience will be considered on an individual basis.
Fees and funding
Tuition feesNo fee information has been provided for this course
Additional fee information
Course contact detailsVisit our course page
UK Postgraduate Admissions Office
024 7765 4321
European and International Admissions Office
+44 024 7765 2152