Overview

Motivation

The emerging phenomena of Big Data - large pools of data sets that can be captured, communicated, aggregated, stored, and analyzed - has presented companies and organisations with trillions of bytes of information about their customers, suppliers, and operations. Millions of networked sensors are also embedded in various devices such as mobile phones and tablet computers to sense, create, and communicate data. Big data is now part of every industry sector and function of the global economy. It is increasingly the case that modern economic activity, innovation, and growth have to take place with data and the related analytic processes, methods and outputs. The discipline of business analytics (BA) enables companies and organisations to realise the full potential of data generated from various business processes, sources and devices, thus improving their speed and effectiveness in generating business insights and intelligence for optimal decision making purposes.

Programme Introduction

The Bachelor of Science (Business Analytics) degree programme is an inter-disciplinary undergraduate degree programme offered by the School of Computing with participation from the Business School, Faculty of Engineering, Faculty of Science, and Faculty of Arts and Social Sciences. This is a four-year direct honours programme which offers a common two-year broad-based inter-disciplinary curriculum where all students will read modules in Mathematics, Statistics, Economics, Accounting, Marketing, Decision Science, Industrial and Systems Engineering, Computer Science and Information Systems. Students in their third and fourth years of study may choose elective modules from two lists of either functional or methodological elective modules. Functional elective modules span business functions or sectors of marketing, retailing, logistics, healthcare, etc. Methodological elective modules include those related to big data techniques, statistics, text mining, data mining, social network analysis, econometrics, forecasting, operations research, etc. In sum, these elective modules span the most exciting and challenging areas of business analytics practice in the industry today.

Programme Learning Objectives

Learning objectives of the Bachelor of Science (Business Analytics) degree programme are:

  • To understand the conceptual and methodological foundations of analytical methods and techniques for business analytics, as referenced from disciplines such as computing, engineering, science, mathematics, statistics, business and economics
  • To appreciate and understand current business analytics problems in the industry worldwide and be able to identify and resolve practically relevant business analytics questions and issues
  • To apply appropriate analytic tools and techniques to resolve complex business analytics problems in various industry sectors and domains
  • To cultivate the practices of independent and group learning on the part of students that will prepare them to function effectively for diverse careers in business analytics

Career Prospects for Business Analytics (BA) Graduates

Graduates of this BA degree programme are expected to have career choices as business intelligence analysts, research analysts, quantitative data modelers, marketing analysts, supply chain optimization analysts, decision science analysts, revenue optimization analysts, business intelligence specialists or engineers, IT business analysts, web analytics consultants, BA consultants, etc. They are expected to find employment in both leading public and private firms and organizations (e.g., SPSS, SAS, Acorn Marketing & Research, The Nielsen Company, Singtel, IBM Research, Google, Facebook, Singapore Airlines) where there are intensive needs for data processing and analyses, as well as business intelligence insights.

 

Curriculum and Admission

Degree Requirements and Curriculum

This programme is offered as a four-year direct honours Bachelor of Science (Business Analytics) degree programme. Upon completion of the core module requirements, students in their third and fourth years of study may choose elective modules from two lists of either functional or methodological elective modules.

Functional elective modules span business functions or sectors of marketing, retailing, logistics, healthcare, etc. Methodological elective modules include those related to big data techniques, statistics, text mining, data mining, social network analysis, econometrics, forecasting, operations research, etc. In sum, these elective modules span the most exciting and challenging areas of BA practice in the industry today.

The core and compulsory components of the BA programme are as follows:

  • Common modules at level 1000/2000 = 64 MCs
  • Common modules at level 3000/4000 = 20 MCs
  • Final-Year Project = 12 MCs

In total, the 160 MCs requirement for graduation are broken down as follows:

  • Core modules = 96 MCs (21 modules x 4 MCs + FYP of 12 MCs)
  • Elective modules = 24 MCs (6 modules x 4 MCs)
  • University level requirements = 20 MCs
  • Unrestricted electives = 20 MCs

This programme offers a common two-year broad-based inter-disciplinary curriculum where all students will read modules in Mathematics, Statistics, Economics, Accounting, Marketing, Decision Science, Industrial and Systems Engineering, Computer Science and Information Systems. After the first two years of studies, students will be equipped with the necessary foundational knowledge to take more specialised modules in their third and fourth years. Please see the section on “Programme Requirements for Bachelor of Science (Business Analytics)” for the list of core and elective course modules in the curriculum.

Admission Requirements

For Diploma Holders:
Selected (on case-by-case basis) Polytechnic Diploma* or Polytechnic Diploma* with at least an A2 grade in GCE O level Elementary Mathematics or at least a B4 grade in GCE O level Additional Mathematics.
*: Students without the relevant A level subject may need to take specified bridging modules (e.g., MA1301 Introductory Mathematics offered by the Faculty of Science).

For A Level Holders:
A good grade in either GCE A level or H2 level or IB higher level Mathematics.

Candidature / Duration

The typical candidature is four years. The maximum candidature is five years.

Continuation and Graduation Requirements

The Bachelor of Science in Business Analytics is a 4-year direct honours programme. The Bachelor of Science in Business Analytics (Honours) degree will be awarded to students who complete 160 MCs and performed well throughout the course, as determined by their Cumulative Average Point. Those who do not qualify for an Honours degree will be awarded a Bachelor of Science in Business Analytics degree.

Proposed Fees

The proposed fees structure are as follows:
Full fees: $34,900
Singapore citizens: $7,460
Singapore permanent residents: $9,850
International students: $13,730

This fees structure follows that of other degree programmes offered in the School of Computing for students admitted in the Academic Year 2012/2013.

Expected Intake

Entry into the programme for the first year will be restricted to 40 students and will be slowly increased to a maximum of 80 students per year at steady state, depending on the quality of the student intake.

 

Programme Structure

Programme Framework (Total MCs = 160)

The core and compulsory components of the BA programme are as follows:

  • Common modules at level 1000/2000 = 64 MCs
  • Common modules at level 3000/4000 = 20 MCs
  • Final-Year Project = 12 MCs

In total, the 160 MCs requirement for graduation are broken down as follows:

  • Core modules = 96 MCs (21 modules x 4 MCs + FYP of 12 MCs)
  • Elective modules = 24 MCs (6 modules x 4 MCs)
  • University level requirements = 20 MCs
  • Unrestricted electives = 20 MCs

 

The detailed BA programme structure and associated modules are presented below.

Level

Programme Reqirements

Cummulative MCs

1000/ 2000 Core modules
(64 MCs)

ACC1002X Financial Accounting
MKT1003X Marketing
EC1301 Principles of Economics
MA1311 Matrix Algebra and Applications, or MA1101R Linear Algebra I1
MA1521 Calculus for Computing, or MA1102R Calculus1
CS1010 Programming Methodology
CS1020 Data Structures and Algorithms I
IS1103 Computing and Society
IS1105 Strategic IT Applications
IS1112 E-Business Essentials or or BT2102 Data Management and Visualisation

IE2110 Operations Research I2, or DSC3214 Introduction To Optimisation
IS2101 Business and Technical Communication#
Either (ST2131 Probability and ST2132 Mathematical Statistics);
or (ST2334 Probability and Statistics and CS2010 Data Structures and Algorithms II)

New multi-disciplinary modules:
BT1101 Introduction to Business Analytics
BT2101 IT and Decision Making

64 MCs

16 x 4 MCs of which:
11 Level 1000 modules
5 Level 2000 modules

 

3000/ 4000 Core modules
(20 MCs)

BT3103 Application Systems Development for Business Analytics or
IS4240 Business Intelligence Systems
DSC3215 Stochastic Models in Management
ST3131 Regression Analysis

BT3101 Business Analytics Capstone Project
BT3102 Computational Methods for Business Analytics*

84 MCs

5 x 4 MCs of which:
4 Level 3000 modules
1 Level 4000 modules

 

Students will choose either option 1 or option 2 below:

Option 1

 

Choose either BT4101 B.Sc. (Business Analytics) Dissertation (12 MCs) or Industrial Experience Requirement@ (12 MCs)


Choose 6 modules to make up 24 MCs from Lists A, B and C, with at least 2 modules each from Lists A and B. 5 of 6 modules must be at level-4000.

List A (Business Applications)
BT4211 Data-Driven Marketing*
BT4212 Search Engine Optimization and Analytics*
IS3240 Economics of E-Business
IS4250 Healthcare Analytics
DSC3224 Dynamic Pricing and Revenue Management
DSC4213 Analytical Tools for Consulting
IE3120 Manufacturing Logistics
MKT4415C Seminars in Marketing: Applied Market Research

List B (Analytics Methods)
CS3244 Machine Learning
BT4221 Big Data Techniques and Technologies
BT4222 Mining Web Data for Business Insights*
IS4241 Social Media Network Analysis
BSP4513 Econometrics: Theory & Practical Business Application
DSC3216 Forecasting for Managerial Decisions
IE4210 Operations Research II
ST4240 Data Mining
ST4245 Statistical Methods for Finance

List C (Technology Implementation)
IS3221 Enterprise Resource Planning Systems
IS3261 Mobile Solutions Design and Development I
S4228 Financial Technology and Analytics

IS4302 Blockchain and Distributed Ledger Technologies

120 MCs

 

Option 2

Read and pass both BT4101 B.Sc. Dissertation  (12 MCs) and Industrial Experience Requirement@ (12 MCs)

Pass 3 modules (worth 12 MCs)  from Lists A, B and C, with at least 1 module each from Lists A and B. 2 of 3 modules must be at level-4000.

List A (Functional):

DSC3224 Dynamic Pricing and Revenue Management
IE3120 Manufacturing Logistics
IS3240 Economics of E-Business
BT4211 Data-Driven Marketing
BT4212 Search Engine Optimization and Analytics
DSC4213 Analytical Tools for Consulting
IS4250 Healthcare Analytics
MKT4415C Seminars in Marketing: Applied Market Research

List B (Methodological):

CS3244 Machine Learning
DSC3216 Forecasting for Managerial Decisions
BSP4513 Econometrics: Theory & Practical Business Application
BT4221 Big Data Techniques and Technologies
BT4222 Mining Web Data for Business Insights
IS4241 Social Media Network Analysis
IE4210 Operations Research II
ST4240 Data Mining
ST4245 Statistical Methods for Finance

List C (Technological):

IS3221 Enterprise Resource Planning Systems
IS3261 Mobile Solutions Design and Development
IS4228 Information Technologies in Financial Services
IS4302 Blockchain and Distributed Ledger Technologies

 120 MCs

University requirements

Any module satisfying University level requirement for total of 20 MCs

140 MCs

Unrestricted electives

Any module satisfying Unrestricted elective condition for total of 20 MCs

160 MCs

 #: Taught by the Centre for English Language Communication. Students who are taking IEM1201x or IEM2201x module on grade basis can use it to replace IS2101.
@: Students can choose to take on either IS4010 Industry Internship Programme (12 MCs) or any current 12 MCs or more internship-related programmes within the School of Computing (e.g., CP3880 Advanced Technology Attachment Programme (ATAP)) and/or within NUS (e.g., Innovative Local Enterprise Achiever Development (iLEAD) and NUS Overseas College (NOC)) to satisfy the industry experience requirement.


Notes:

1 : Students are encouraged to take these MA module options should they wish to pursue a more rigorous treatment of the subject topics covered.
2 : Students are encouraged to take IE2110 should they wish to choose IE4210 as an elective module.
  

Programme Study Schedule

Sample Study Plan 1

bastudyplan1

 

Sample Study Plan 2

bastudyplan2

 

Sample Study Plan 3

bastudyplan3

 

Notes:

  • Study schedule is based on current information and may change depending on module mounting.
  • This is just a recommended sample study plan and need not be followed strictly. The study schedule can be varied or modified according to a student’s desired pace of programme completion and other additions such as UROP or USP participations.
  • Suggested methodological elective module ==> functional elective module paths
    • BT4221 Big Data Techniques and Technologies + ST4240 Data Mining ==> BT4211 Data-Driven Marketing / MKT4415C Seminars in Marketing: Applied Market Research
    • DSC3216 Forecasting for Managerial Decisions ==> DSC3224 Dynamic Pricing and Revenue Management / DSC4213 Analytical Tools for Consulting / IE3120 Mfg Logistics
    • BT4221 Big Data Techniques and Technologies ==> BT4212 Search Engine Optimization and Analytics
    • ST4240 Data Mining ==> IS4250 Healthcare Analytics

Legend:

  • ULR = University Level Requirements; PE = Programme Electives; UE = Unrestricted Electives
  • Cell shaded with light blue denotes a core module which is also a prerequisite for another core module.
  • Cell shaded with light pink denotes a core module which is also a prerequisite for another elective module.
  • Each pair of coloured squares across two cells indicates a prerequisite chain. For example, indicates that ST3131 is a prerequisite for BT3101, and indicates that DSC3215 is another prerequisite for BT3101.
  • The checkered square in a cell, , indicates that this core module is a prerequisite for another elective module.


NUS Overseas Colleges (NOC) – Business Analytics

Students who attended NOC programme may:

  • count TR3201 Entrepreneurship Practicum (8 MCs) partially in lieu of one Business Analytics programme elective at level-3000 (4 MCs).
  • count TR3202 Start-up Internship Programme (12 MCs) towards Industrial Experience Requirement  (i.e. IS4010 Industry Internship Programme)
  • count TR3203 Start-up Case Study and Analysis (8 MCs) towards unrestricted electives.


University Scholars Programme (Business Analytics)

Students in the University Scholars Programme (USP) who choose the Bachelor of Science (Business Analytics) degree programme will do so with the following variations:

  • They will not be required to read IS2101 Business and Technical Communication in the Core modules requirement. It is replaced by USP Foundation module of Writing and Critical Thinking.
  • They will read the UROP module (CP3208) in place of the Business Analytics Capstone Project module (BT3101) in the Core modules requirement. CP3208 is an independent study module (ISM) which will be counted as 1 USP Inquiry module in the Sciences and Technologies domain.
  • They will not be required to read University Level Requirements (20 MCs). These are replaced by the 3 USP Inquiry modules and 2 USP Foundation modules (Quantitative Reasoning and University Scholars Seminar).
  • They will not be required to read Unrestricted Electives (20 MCs). These are replaced by the USP Reflection module of Senior Seminar and 4 USP Inquiry modules.
  • In summary, the breakdown of 12 USP modules will fit into these MCs requirement categories:
    • Core: 1 Foundation module (Writing and Critical Thinking replacing IS2101), 1 Inquiry module (CP3208/USP-ISM replacing BT3101)
    • ULR: 3 Inquiry modules and 2 Foundation modules
    • UE: 1 Reflection module and 4 Inquiry modules