Business

Master of Science in Business Analytics

The Master of Science in Business Analytics is a postgraduate programme that prepares professionals for advanced practice in data-driven decision-making, business intelligence, and predictive analytics. The programme combines statistical analysis with business strategy and data technology application.

Core areas include business analytics, data mining, predictive modelling, machine learning, data visualisation, business intelligence, statistical analysis, optimisation, research methods, and thesis. Students engage with both analytical theory and practical business data analysis through coursework and research.

The programme is offered by JKUAT as a public institution, and Strathmore University and USIU-Africa as private institutions. Programmes are offered over two academic years through full-time and part-time modes of study.

Students develop competencies in business analytics, data mining, predictive modelling, machine learning, data visualisation, business intelligence, statistical analysis, optimisation, and research methods. The programme includes coursework, examinations, practical projects, and a research thesis or project.

JKUAT charges approximately KES 254,100/year (KES 508,200 total) for related business computing programmes. Strathmore University charges approximately KES 305,000/year (KES 610,000 total) for data science and analytics programmes. Entry requires a Bachelor's degree with Second Class Honours Upper Division in business, statistics, computer science, mathematics, or related fields from a recognised university.

Graduates pursue careers as business analysts, data scientists, analytics managers, business intelligence analysts, quantitative analysts, and consultants across corporations, financial institutions, technology companies, consulting firms, and government agencies.

Skills Required

Business Analytics and Data-Driven Decision Making
Data Mining and Pattern Discovery
Predictive Modelling and Forecasting
Machine Learning for Business Applications
Data Visualisation and Dashboard Design
Business Intelligence and Reporting
Statistical Analysis and Hypothesis Testing
Optimisation and Operations Research
Research Methods in Business Analytics
Academic Writing and Thesis Research

Key Subjects

Business Analytics and Data-Driven Decision Making
Data Mining and Pattern Discovery
Predictive Modelling and Forecasting
Machine Learning for Business Applications
Data Visualisation and Dashboard Design
Business Intelligence and Reporting
Statistical Analysis and Hypothesis Testing
Optimisation and Operations Research
Research Methods in Business Analytics
Thesis Research

Certifications

SAS Business Analytics Certification
Microsoft Power BI Certification

Specializations

Marketing Analytics

Focuses on marketing analytics, covering customer segmentation, market basket analysis, campaign analysis, customer lifetime value, and managing marketing analytics.

Financial Analytics

Examines financial analytics, covering risk modelling, credit scoring, fraud detection, portfolio optimisation, and managing financial analytics.

Operations Analytics

Covers operations analytics, covering supply chain analytics, inventory optimisation, process improvement, demand forecasting, and managing operations analytics.

HR Analytics

Focuses on HR analytics, covering workforce analytics, performance prediction, attrition modelling, talent analytics, and managing HR analytics.

Healthcare Analytics

Examines healthcare analytics, covering patient outcomes, resource optimisation, disease prediction, health informatics, and managing healthcare analytics.

Text Analytics and NLP

Covers text analytics, covering sentiment analysis, text mining, natural language processing, social media analytics, and managing text analytics.

Duration: 2 years
Public, up to: Ksh 254,100
Private, up to: Ksh 305,000
Job market: Very high

The programme

What you study, how long it takes, and how it is delivered.

Practicalities

Study mode: Full-time, Part-time
Attachment: 0 months
Average class: 25 students
Award: Masters

What you study

10 subjects

Business Analytics and Data-Driven Decision Making
Data Mining and Pattern Discovery
Predictive Modelling and Forecasting
Machine Learning for Business Applications
Data Visualisation and Dashboard Design
Business Intelligence and Reporting
Statistical Analysis and Hypothesis Testing
Optimisation and Operations Research
Research Methods in Business Analytics
Thesis Research

Modules

12 in the programme

Business Analytics and Data-Driven Decision Making
Year 1Semester 13 creditsCore
Examines data-driven decision-making, KPI design, analytics strategy, business problem framing, and managing business analytics.
Data Mining and Pattern Discovery
Year 1Semester 13 creditsCore
Covers association rules, clustering, classification, anomaly detection, text mining, and managing data mining.
Research Methods in Business Analytics
Year 1Semester 13 creditsCore
Covers research design, data collection, analysis, ethical issues, and conducting analytics research, preparing students for their thesis.
Predictive Modelling and Forecasting
Year 1Semester 23 creditsCore
Examines regression, time series forecasting, ARIMA, exponential smoothing, model evaluation, and managing predictive modelling.
Machine Learning for Business
Year 1Semester 23 creditsCore
Covers supervised learning, unsupervised learning, neural networks, decision trees, ensemble methods, and managing machine learning.
Data Visualisation and Dashboard Design
Year 1Semester 23 creditsCore
Examines dashboard design, ggplot, Tableau, Power BI, interactive visualisation, storytelling, and managing data visualisation.
Business Intelligence and Data Warehousing
Year 1Semester 23 creditsCore
Covers data warehousing, ETL, OLAP, reporting, BI architecture, data governance, and managing business intelligence.
Statistical Analysis and Optimisation
Year 2Semester 13 creditsCore
Examines hypothesis testing, ANOVA, regression, linear programming, integer programming, simulation, and managing statistical analysis and optimisation.
Marketing and Customer Analytics
Year 2Semester 13 creditsCore
Covers customer segmentation, market basket analysis, campaign analysis, churn prediction, customer lifetime value, and managing marketing analytics.
Financial and Risk Analytics
Year 2Semester 13 creditsCore
Examines risk modelling, credit scoring, fraud detection, portfolio optimisation, and managing financial analytics.
Big Data and Cloud Analytics
Year 2Semester 13 creditsCore
Covers big data technologies, Hadoop, Spark, cloud platforms, distributed computing, real-time analytics, and managing big data analytics.
Research Project or Thesis
Year 2Semester 26 creditsCore
Original research project or thesis on a business analytics topic, demonstrating mastery of research methods and analytics knowledge, assessed through written submission and oral defence.

Specialisations

Marketing Analytics
Focuses on marketing analytics, covering customer segmentation, market basket analysis, campaign analysis, customer lifetime value, and managing marketing analytics.
Financial Analytics
Examines financial analytics, covering risk modelling, credit scoring, fraud detection, portfolio optimisation, and managing financial analytics.
Operations Analytics
Covers operations analytics, covering supply chain analytics, inventory optimisation, process improvement, demand forecasting, and managing operations analytics.
HR Analytics
Focuses on HR analytics, covering workforce analytics, performance prediction, attrition modelling, talent analytics, and managing HR analytics.
Healthcare Analytics
Examines healthcare analytics, covering patient outcomes, resource optimisation, disease prediction, health informatics, and managing healthcare analytics.
Text Analytics and NLP
Covers text analytics, covering sentiment analysis, text mining, natural language processing, social media analytics, and managing text analytics.

A day as a student

A typical day during the MSc in Business Analytics programme combines lectures, computer laboratory sessions, case study workshops, seminars, and independent study. Sessions cover business analytics, data mining, predictive modelling, machine learning, and data visualisation. Business analytics sessions examine data-driven decision-making, KPI design, analytics strategy, business problem framing, and managing business analytics. Data mining sessions cover association rules, clustering, classification, anomaly detection, text mining, and managing data mining. Predictive modelling sessions cover regression, time series forecasting, ARIMA, exponential smoothing, and managing predictive modelling. Machine learning sessions cover supervised learning, unsupervised learning, neural networks, decision trees, ensemble methods, and managing machine learning. Data visualisation sessions cover dashboard design, ggplot, Tableau, Power BI, interactive visualisation, and managing data visualisation. Business intelligence sessions cover data warehousing, ETL, OLAP, reporting, BI architecture, and managing business intelligence. Statistical analysis sessions cover hypothesis testing, ANOVA, regression, non-parametric methods, and managing statistical analysis. Optimisation sessions cover linear programming, integer programming, network optimisation, simulation, and managing optimisation. Marketing analytics sessions cover customer segmentation, market basket analysis, campaign analysis, churn prediction, and managing marketing analytics. Financial analytics sessions cover risk modelling, credit scoring, fraud detection, portfolio optimisation, and managing financial analytics. Research methods sessions prepare students for their thesis, covering research design, data collection, and analysis. Computer laboratory sessions provide hands-on experience with Python, R, SAS, Tableau, Power BI, SQL, and machine learning tools. Case study workshops provide hands-on experience with real-world business datasets, analytics projects, and dashboard development. Seminars and discussion groups provide opportunities for debating current issues in business analytics. Guest lectures from experienced data scientists, business analysts, and industry professionals provide practical insights. The programme culminates in a research project or thesis on a business analytics topic.

The trade offs

In its favour

Very high demand for business analytics professionals with growing data-driven decision-making, digital transformation, and technology adoption in Kenya.
Programme offered by both public (JKUAT) and private (Strathmore, USIU-Africa) universities, providing institutional choice.
JKUAT offers competitive fees at approximately KES 254,100/year for related business computing programmes.
Programme combines statistics, computing, and business strategy, providing versatile interdisciplinary skills.

Against it

Strathmore University (private) charges higher fees at approximately KES 305,000/year.
The exact programme name may vary across institutions, potentially causing confusion for prospective students.
Programme requires quantitative, business, or computing background, which limits access for non-related graduates.
Rapidly evolving field requires continuous self-learning beyond the programme curriculum.

What it costs

Tuition at both ends of the market, and how to pay for it.

What it costs, and where

Against 331 business courses

Public254k to 254k

254k at JKUAT254k at JKUAT

Private238k to 305k

238k at KCA University305k at Strathmore University

Annual tuition in Kenyan shillings, rounded. The upright tick is the median for this field, so a bar sitting entirely to its right is an expensive programme by the standards of its own subject.

The fine print

JKUAT 254,100/yr unverified specific. KCA, Strathmore unverified for Business Analytics.

HELB postgraduate loans are available for Kenyan students. JKUAT may offer postgraduate scholarships for eligible students. Strathmore University may offer financial aid for eligible students. Some technology companies may sponsor staff for postgraduate study in analytics.

Funding options

HELB Postgraduate Loan
JKUAT Postgraduate Scholarship
Strathmore Financial Aid

Scholarships

3 recorded

HELB Postgraduate Loan
LoanKsh 200,000Kenyan
Kenyan students pursuing postgraduate studies at recognised universities.
JKUAT Postgraduate Scholarship
ScholarshipKsh 150,000Kenyan
JKUAT offers postgraduate scholarships for eligible students in computing programmes.
Strathmore Financial Aid
ScholarshipKsh 200,000Kenyan
Strathmore University offers financial aid for eligible postgraduate students.

Getting in

The grades, the alternatives, and who accredits the award.

What you need

KCSE mean grade: N/A (Postgraduate)
Alternative entry: Most universities require Upper Second Class Honours in business, statistics, computer science, or related fields. Lower Second Division holders with relevant experience are considered. USIU-Africa requires adequate computing units for mathematical sciences graduates. Contact respective universities for specific admission requirements.

How you are assessed

4 components

Coursework and Continuous Assessment
Coursework30% of the mark
Continuous assessment through coursework assignments, case studies, laboratory reports, seminar presentations, and class participation.
Written Examinations
Examination40% of the mark
Written examinations covering business analytics, data mining, predictive modelling, machine learning, and statistical analysis.
Practical Project and Laboratory Assessment
Practical30% of the mark
Practical assessment through data analysis projects, dashboard development, machine learning implementation, and demonstrating analytics skills.
Research Project or Thesis
Research100% of the mark
Original research project or thesis on a business analytics topic, demonstrating mastery of research methods and analytics knowledge, assessed through written submission and oral defence.

Accreditation

The programme is accredited by the Commission for University Education (CUE). JKUAT (public), Strathmore University and USIU-Africa (private) offer MSc in Business Analytics or related programmes. All programmes meet CUE standards for postgraduate training in business analytics and data science. USIU-Africa also holds dual accreditation with WASC Senior College and University Commission (WASCUC) in the USA. Graduates are eligible for SAS Business Analytics certification and Microsoft Power BI certification.

Accredited by

Commission for University Education (CUE)
Academic accreditationRequired
Programme accredited by CUE. JKUAT (public), Strathmore University and USIU-Africa (private) offer MSc in Business Analytics or related programmes. All programmes meet CUE standards for postgraduate training in business analytics and data science. USIU-Africa also holds dual accreditation with WASC Senior College and University Commission (WASCUC) in the USA. Graduates are eligible for SAS Business Analytics certification and Microsoft Power BI certification.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

6 roles

Business Analyst
Very high demandKsh 150,000 to Ksh 600,000
Conducts business analysis, overseeing requirements analysis, process modelling, data analysis, stakeholder management, and managing business analytics.
Data Scientist
Very high demandKsh 180,000 to Ksh 700,000
Conducts data science work, overseeing data analysis, machine learning, predictive modelling, and managing data science.
Analytics Manager
High demandKsh 200,000 to Ksh 800,000
Manages analytics teams, overseeing analytics strategy, project management, team leadership, and managing analytics operations.
Business Intelligence Analyst
High demandKsh 150,000 to Ksh 600,000
Develops BI solutions, overseeing dashboard design, reporting, data warehousing, and managing business intelligence.
Quantitative Analyst
High demandKsh 170,000 to Ksh 650,000
Applies quantitative methods, overseeing statistical modelling, risk analysis, optimisation, and managing quantitative analysis.
Analytics Consultant
High demandKsh 180,000 to Ksh 700,000
Provides analytics consulting, overseeing client engagement, solution design, implementation, and managing analytics consulting.

Graduate outcomes

Where these fields lead

8 careers

Tools you will learn

Python
SoftwarePrimary
Python for data analysis and machine learning, covering pandas, numpy, scikit-learn, matplotlib, and managing data science.
R
Software
R for statistical analysis, covering statistical modelling, data visualisation, time series, and managing statistical computing.
Tableau
Software
Tableau for data visualisation, covering dashboard design, interactive visualisation, data exploration, and managing data visualisation.
Power BI
Software
Microsoft Power BI for business intelligence, covering dashboards, reporting, DAX, data modelling, and managing business intelligence.

Industry links

Common misconceptions

Business analytics is just about making charts.
Business analytics covers comprehensive statistical analysis, predictive modelling, machine learning, optimisation, and data-driven strategy beyond just making charts.
This programme is only for those with IT backgrounds.
Business analytics skills are valuable for business, finance, marketing, operations, HR, and healthcare professionals who want to leverage data.
Business analytics is the same as data science.
While related, business analytics focuses more on business decision-making, KPIs, and strategy, while data science focuses more on algorithms, programming, and infrastructure.
Machine learning is just about building models.
Machine learning covers comprehensive data preparation, feature engineering, model selection, validation, deployment, monitoring, and ethics.
Data visualisation is just about making dashboards look good.
Data visualisation covers comprehensive visual perception, dashboard design, interactive visualisation, storytelling, and effective communication.
Business intelligence is just about reporting.
Business intelligence covers comprehensive data warehousing, ETL, OLAP, data governance, self-service analytics, and BI architecture.