Business – Master of Analytics (MAnalyt)

Programme Overview

The Master of Analytics (Business) is a professional qualification designed to turn data into a strategic business asset. The programme is uniquely grounded in real-world contexts, focusing on the entire analytics life cycle: from identifying business problems and acquiring data to deploying machine learning models and communicating insights to stakeholders. It is specifically built to meet the high industry demand for graduates who can bridge the gap between technical data science and commercial decision-making.

What You'll Study

Part One: Core Compulsory (60 credits)

• Data Mastery: Scripting (R/Python), databases (SQL), and data privacy/ethics.
• Multivariate Analysis: Visualisation and factor analysis for big data.
• Practical Data Mining: Supervised/unsupervised modelling and clustering.
• Applied Econometric Methods: Specification and validation of forecasting models. Part One: Business Specialisation (60 credits)
• Option A – Marketing: Customer Insights and Return on Marketing Investment.
• Option B – Finance: Big Data in Finance & Banking and Managerial Finance. Part Two: Applied Project (60 credits)
• Professional Practicum: 600+ hours of work-integrated learning within an organisation, solving a real-life analytics problem.

Why Choose This Programme?

• Triple Crown Excellence: Delivered by Massey Business School, ranked in the top 5% of business schools globally (AACSB, AMBA, EQUIS).
• Work-Integrated Learning: The 60-credit project allows you to gain New Zealand work experience before graduation.
• Software Proficiency: Hands-on experience with industry-standard tools including SAS, R, Python, and SQL.
• Progression Path: Direct pathway for those with a non-analytics background to pivot into high-growth data roles.

Entry Requirements

• Academic: A relevant Bachelor's degree with a minimum B- grade average in higher-level courses.
• Experience Alternate: A Bachelor's degree in any field plus at least 2 years of relevant professional experience.
• Technical: Sufficient background in statistical analysis tools (assessed via CV and transcripts).
• English: IELTS 6.5 | TOEFL iBT 90 | PTE 58 | Duolingo 120.
  

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