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Lead with data. Decide with confidence.
Online or on campus
The MSc Business Analytics at Haverton is designed for ambitious analysts, product leaders, and consultants who need more than dashboards — you must frame decisions, build reproducible pipelines, deploy models responsibly, and communicate findings to executives under uncertainty. Unlike a pure data science degree, this programme emphasises **business impact**: marketing analytics, financial forecasting, prescriptive optimisation, and analytics governance aligned with UK GDPR and EU AI Act literacy. Each module combines faculty-led video sessions, case-based assignments, and tools used in enterprise analytics teams (SQL, Python, Power BI/Tableau, cloud warehouses). The capstone is a sponsored consulting engagement with a live brief, faculty mentorship, and industry panel review. MSc Business Analytics is taught as one award, not a list of unrelated modules. The published length is 24 months, and the credit total is 36. Students move from Business Analytics Foundations & Decision Science through Business Analytics Foundations & Decision Science; Statistical Methods for Business Analytics; Data Management, SQL & Analytics Engineering; Data Visualization & Executive Storytelling; Predictive Analytics & Machine Learning for Business; Optimization & Prescriptive Analytics, and finish on MSc Business Analytics Capstone Project. Each course has a question, a method, and a submission. In this field, students define a measurable question, fit a method that can be checked, and report where it fails. Reading is a dataset description, a methods note, and one published evaluation. The artefact a marker expects is a project note with the question, the method, the result, and the limitation. The award is built so that a graduate can do the following in practice: Frame complex business problems as structured analytics engagements with clear KPIs Apply statistical inference, regression, and experimentation to commercial decisions Engineer trustworthy SQL pipelines and dimensional models for BI and ML Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.
Every module is built for professionals who must influence decisions — not only build models. You will maintain a portfolio repository (SQL, notebooks, dashboards, governance artefacts) reviewed by faculty and presented to an industry panel in the capstone. Haverton partners with retail and fintech sponsors for anonymised capstone datasets.
Faculty spotlight
Dr. Raj Patel leads cloud analytics architecture; Professor Margaret Ashford supervises capstone engagements with emphasis on executive communication and governance.
Study online
Online tuition is free. Online examinations and certificates are 100% free and sponsored.
On-campus study
Prefer to learn at our London campus? Campus tuition is published on each programme page. All examinations are 100% free of charge.
| Code | Course | Credits · hours |
|---|---|---|
| MSBA501 | Business Analytics Foundations & Decision Science Business Analytics Foundations & Decision Science (MSBA501) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA502 | Statistical Methods for Business Analytics Statistical Methods for Business Analytics (MSBA502) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA503 | Data Management, SQL & Analytics Engineering Data Management, SQL & Analytics Engineering (MSBA503) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA504 | Data Visualization & Executive Storytelling Data Visualization & Executive Storytelling (MSBA504) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| Code | Course | Credits · hours |
|---|---|---|
| MSBA505 | Predictive Analytics & Machine Learning for Business Predictive Analytics & Machine Learning for Business (MSBA505) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA506 | Optimization & Prescriptive Analytics Optimization & Prescriptive Analytics (MSBA506) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA507 | Big Data, Cloud Analytics & Modern Data Platforms Big Data, Cloud Analytics & Modern Data Platforms (MSBA507) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA508 | Marketing, Customer & Digital Analytics Marketing, Customer & Digital Analytics (MSBA508) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA509 | Financial Analytics, Forecasting & Risk Modeling Financial Analytics, Forecasting & Risk Modeling (MSBA509) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| Code | Course | Credits · hours |
|---|---|---|
| MSBA601 | Analytics Strategy, Ethics, Governance & AI Policy Analytics Strategy, Ethics, Governance & AI Policy (MSBA601) is a course on MSc Business Analytics. It carries 15 credits and 150 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 15 · 150 h |
| MSBA602 | MSc Business Analytics Capstone Project MSc Business Analytics Capstone Project (MSBA602) is a course on MSc Business Analytics. It carries 30 credits and 300 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 30 · 300 h |
Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.
The published duration is 24 months. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.
You may study this award fully online from your country, or — where published — on campus at Haverton. Online study does not require a student visa. Campus study may.
Degree tuition for this award is published as £0 / tuition-free on the online pathway. All online degree examinations and certificates are 100% free and sponsored — the only cost for online study is the application fee. Campus tuition and campus examinations are charged separately. Check the Fees page for details.
Requirements are grouped on this page (academic, English, documents). Equivalent qualifications are considered. English may be waived after prior English-medium study.
Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.
Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. Haverton University publishes verification pages for certificates. We do not claim automatic equivalence in every country.
Start an application on this website. Progress is saved from the first step. Admissions: admissions@haverton.org.
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