Business Analytics

Overview

The increase in the volume, variety, and velocity of data creates opportunities for businesses to improve decision making and develop new data driven products and services. The MSc Business Analytics has been developed to meet the demand for qualified professionals, who possess the necessary expertise to realise end-to-end business analytics solutions and are equipped to utilise data for business decision-making purposes.



The programme is built around the three core areas needed to succeed in analytics: business knowledge, statistics, and computing. This includes modules focusing on the application of analytics in core business functions such as marketing and human resources, as well as modules focusing on developing and applying technical skills such as advanced analytics and machine learning, text mining, data management, and data driven decision making.



In total, students will study eight modules in addition to pre-course training and a final dissertation project. The dissertation is a key highlight of the programme, as it provides students with the opportunity to undertake an independent project where they will create a technical business analytics solution incorporating all elements of the programme.



The programme will include an induction, where pre-course training in key statistics and computer skills will ensure students from a range of backgrounds have the necessary skills to undertake the course.

MSc Business Analytics students can expect to study the following modules:



Semester 1

Statistics for Business

Data Management

HR Analytics

Artificial Intelligence in Business and Society



Semester 2

Advanced Analytics and Machine Learning

Data Mining

Data Driven Decision Making

Marketing Analytics



Semester 3

*Dissertation

The dissertation provides students with the opportunity to undertake an independent project. This will involve the development of a technical business analytics solution incorporating elements from the course. The suggested technologies for the solution will be those covered in the course. The solution should typically include a combination of a database, machine learning, and a visualisation component. It is recognised that in some cases projects may focus on specific components (e.g. storage and processing, predictive analytics, or advanced visualisation and interpretation), and this should be agreed in advance. Students will also be provided with suggestions around potential data sources for use in the project.



In addition to the technical solution, students will be required to produce an initial feasibility study, a technical report, and a written report include a review of the literature, methodology for solving the problem, and results, discussion and conclusions. The module requires students to draw from across the course, incorporating knowledge from the three core business analytics domains: statistics, computing, and business.

Graduate

Normally a 2.1 Honours degree or equivalent qualification acceptable to the University in any discipline to include one module in a quantitative area*. Relevant employment experience in a quantitative area may be considered in lieu of a module in a quantitative area and will be considered on a case-by-case basis.



*This could be a course or module in a broad range of quantitative areas such as Finance, Mathematics, Statistics, Economics, Accounting, Engineering or Physics. Equivalent content from across multiple modules will also be considered.

Applicants are advised to apply as early as possible and ideally no later than 15th August 2025 for courses which commence in late September. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal prior to the deadline stated on course finder. Notifications to this effect will appear on the application portal against the programme application page.



Please note: international applicants will be required to pay a deposit to secure a place on this course.

Assessments will focus on both theory and practical application of business analytics, including the use of data to gain business insights, the development of analytics solutions, essays and group work. It is anticipated that students will have approximately 30 hours direct academic contact time (drawing on methods outlined above) per module. In addition to the direct teaching hours per module, each student will normally be expected to spend approximately 120 hours on individual study time plus time for assessment completion, per module.

1 year (Full Time)

Entry Year: 2025/26

Career Prospects

The programme will appeal to students who intend to pursue a career in a business analytics related field, such as data science, business intelligence, consultancy, informatics, or decision intelligence.



For further opportunities to enhance your studies and career prospects please see the school website.

https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/