Business Analytics
MSc

Our MSc Business Analytics covers a combination of technical skills, critical thinking skills and soft skills.

This programme will train you in analytical decision-making. Not only do you learn the theory of business analytics, but also how to apply it in practice. This involves generating relevant business insights using data-driven methodologies and tools. Our programme is one of the few to teach the entire business analytics life cycle, covering descriptive, predictive and prescriptive analytics.

You will enhance your programming in both R and Python, the two most popular languages in the areas of machine learning, statistics and data mining.

You will strengthen your skills in statistics, data analytics and visualisation. You will improve your problem structuring and problem solving. You will also hone your presentation, negotiation, and leadership skills.

All these skills enable you to develop the competence and confidence to contribute to the grand challenges faced by organisations.

Programme structure: We continually review and enhance our curriculum to ensure we are delivering the best possible learning experience, and to make sure that the subject knowledge and transferable skills you develop will prepare you for your future. The University will make every reasonable effort to offer programmes and modules as advertised. In some cases, changes may be necessary and may result in new modules or some modules and combinations being unavailable. Not all optional modules are available every year.

Operational Research and Prescriptive Analytics

In this module, you will be introduced to business analytics, management science, and related disciplines, with a particular emphasis on the modelling and solution of real-world problems.
By the end of this module, you will be able to:

• Understand business analytics, management science, and their connections with other disciplines
• Appreciate the power and limitations of analytical techniques, particularly prescriptive ones, when addressing issues and problems in organisations
• Build analytical models of problems and issues in organisations
• Apply specific quantitative techniques appropriately and select the right technique for a given context
• Implement analytical models using spreadsheet software

Statistics and Descriptive Analytics

In this module, you will explore a range of statistical methods motivated by real-world business problems, building your ability to select and apply appropriate techniques to address practical challenges across a variety of business contexts.
By the end of this module, you will be able to:

• Understand probability and statistical arguments
  Understand the hypothesis testing mechanism and its application in business contexts
• Select appropriate statistical methods for a range of important business applications
• Apply a range of statistical methods to a variety of business problems
• Build a cross-sectional regression model using R and interpret the output, including the use of regression diagnostics
• Discuss the strengths and weaknesses of particular statistical approaches and the practical implications of statistical analysis

Programming for Data Scientists

In this module, you will develop the programming skills needed to handle complex data science problems, whether you are completely new to programming or an experienced programmer looking to extend your existing skills. You will learn the fundamentals of programming alongside data processing techniques, including visualisation and statistical data analysis. The module also covers problem solving and the development of graphical applications, providing a broad formation to equip you for the most demanding data science tasks.
By the end of this module, you will be able to:

• Develop programs to solve data science problems in an automated and systematic way
• Handle complex datasets that cannot easily be analysed manually
• Write programs using existing libraries and develop your own libraries where appropriate
• Understand fundamental programming concepts and important abstract data types
• Apply your knowledge of programming languages to learn new ones independently

Analytics in Practice

In this module, you will develop analytical thinking at a holistic level and the ability to conduct analytical projects in a real-world context.
By the end of this module, you will be able to:

• Engage in the process of scoping unstructured business problems, considering both the people involved and their roles, and the aspects of the problem to be analysed
• Identify opportunities for applying analytics across different business contexts
• Demonstrate a critical understanding of the impact of analytics tools and methodologies in support of decision making
• Evaluate the suitability of different combinations of analytics tools for a specific context or application
• Communicate the benefits of using analytics to both technical and non-technical audiences

Optimisation and Heuristics

In this module, you will explore the theory, applications, algorithms, and software tools used in optimisation, with examples drawn from analytics, finance, and data science.
By the end of this module, you will be able to:

• Formulate problems as optimisation problems and solve them
• Appreciate the power and limitations of optimisation methods
• Carry out sensitivity analysis to assess the robustness of a recommended solution
• Use commercial optimisation packages effectively
• Work with at least one modelling language for optimisation
• Identify major heuristic techniques and know when and how to apply them

Intelligent Data Analysis and Visualisation

In this module, you will be introduced to the fundamental methods and approaches from the interrelated areas of data mining, statistical and machine learning, and intelligent data analysis. You will cover the entire data analysis process, from the formulation of a project objective and developing an understanding of available data and resources, through to statistical modelling and performance assessment.
By the end of this module, you will be able to:

• Understand how to approach a data mining and statistical modelling problem in a real-world context
• Apply visualisation methods to obtain insights from data
• Understand the classification problem and the advantages and limitations of different methods used to solve it
• Assess the performance of classification methods
  Use R for visualisation and the estimation of statistical models

Forecasting and Predictive Analytics

In this module, you will be introduced to the topic of forecasting in business organisations, exploring issues concerned with forecasting model building in regression and its extensions. You will also examine forecasting as it applies to operations and how forecasting can best be improved in an organisational context.
By the end of this module, you will be able to:

• Build and assess causal and time series models, evaluating their accuracy and robustness, and apply them to real-world problem domains
• Prepare methodologically sound, clear, and concisely presented reports communicating forecasting results to clients

Transportation and Logistics Modelling

In this module, you will develop the ability to understand and apply mathematical models in making strategic, tactical, and operational logistics decisions. You will be introduced to emerging logistical concepts and explore the associated mathematical modelling approaches required to address them.
By the end of this module, you will be able to:

• Recognise basic logistics models when encountering real problems or reading an algebraic formulation
• Write algebraic formulations for problems related to those studied in the module
• Use professional software to solve and interpret moderately sized instances of problems with reasonably straightforward algebraic formulations
• Implement basic heuristics to find near-optimal solutions for problems where algebraic formulations are inherently complex, such as the vehicle routing problem

Dissertation (Industry)

At the end of the taught modules, you will complete either an applied project, working on a real problem with an organisation from the public or private sector, or a supervised research project, allowing you to investigate a specific topic in depth and engage with the emerging state of the art in your chosen area.

Dissertation (Research)

At the end of the taught modules, you will complete either an applied project, working on a real problem with an organisation from the public or private sector, or a supervised research project, allowing you to investigate a specific topic in depth and engage with the emerging state of the art in your chosen area.

Programme structure: We continually review and enhance our curriculum to ensure we are delivering the best possible learning experience, and to make sure that the subject knowledge and transferable skills you develop will prepare you for your future. The University will make every reasonable effort to offer programmes and modules as advertised. In some cases, changes may be necessary and may result in new modules or some modules and combinations being unavailable. Not all optional modules are available every year.

MSc Direct Entry

Academic:

2:2 Hons degree UK or equivalent.

Specific degree background is required: Completed degree with quantitative methods content (business, engineering, mathematics, sociology etc.)

For specific national curriculum, please view the website.

English:

IELTS 6.5 overall (no band below 6.0)
For other accepted English language tests, please view the website.

Pre-Master’s entry

Applicants who do not meet stated MSc direct entry requirements, may start with a Pre-Master’s programme. Please view full entry requirements here.

Teaching is delivered via a combination of small group lectures and group-based tutorial coursework (oral and written presentation), and assessment is via individual coursework (oral and written presentation) and examinations. You will be encouraged throughout to undertake independent study to supplement what is being taught/learnt and to broaden your personal knowledge.

All modules are delivered in a block teaching, allowing students to concentrate on each subject. All teaching is conducted in English.

German language skills are not required for admission into the programme. You will learn in English, and converse with classmates and academics in English.

All MSc Business Analytics students will receive their postgraduate degree from Lancaster University’s Bailrigg campus in the UK.

• Fees: 

Our tuition fee is set for a 12-month time frame encompassing one academic year.

There are two types of fees at Lancaster University Leipzig:

1.  EU/UK fee status: applicable to citizens of EU/UK and EEA member countries
2.  International fee status: applicable to citizens of the rest of the world

The tuition fee that you will pay depends on your citizenship or your immigration status. International citizens with legal residence in the EU/UK or a EEA member country will be assessed for EU/UK fee status on a case by case basis. The admissions department will provide you with more guidance regarding the fee status review during the application assessment stage. 

• Funding: 

Eligible students may benefit from various funding options available at Lancaster University Leipzig. Explore what options you may be qualified for.

A Business Analytics degree can be widely applied across the business world. Our graduates at Lancaster University UK go on to work for a wide range of companies, large and small, around the world, in a variety of roles.

Recent graduate destinations include:

• Virgin Atlantic
• Avanti West Coast
• EY
• Amazon

The roles our graduates have taken on include:

• Data Scientist
• Business Analyst
• Insights Analyst
• Account Executive
• Financial Analyst
• eCommerce Data Analyst
• Customer Analyst
• Strategy Analyst
• Product Analyst
• Fraud Specialist
• Business Intelligence Developer
• Business Consultant
• Credit Analyst

With data-driven decision-making now central to business success, the demand for professionals skilled in business analytics is rapidly rising across industries. MSc Business Analytics graduates are equipped with a powerful blend of analytical, technical, and strategic skills, enabling them to transform data into actionable insights. This makes them highly valuable in sectors such as finance, healthcare, retail, technology, and consulting. As organisations continue to invest in data capabilities, MSc Business Analytics graduates are exceptionally well-positioned to drive innovation and shape strategic decisions in an evolving business landscape.

For information, visit the Careers Centre at Lancaster University Leipzig.