LEE Wee Leong

Associate Professor of Information Systems (Education) &

Programme Director, MITB(Analytics)

Leading

Business with

Data

1

Master of IT in Business (Analytics)

2

How Do We Make Decisions?

3

*40% of major decision making are based on gut feeling!* Accenture, 2008

12% - Hard Facts88% - Gut Feel* Aspect Consulting, 1997

10% - Hard Facts90% - Gut Feel* Economist Intelligence Unit, 2014

What is Data Analytics?

4

Analytics is the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.

~ Thomas H. Davenport ~ Competing on Analytics: The New Science of Winning

Statistical &Quantitative

Analyses

Explanatory &Predictive Modeling

Fact-based Management

Decisions & Actions

DATA

Why Data Analytics is “HOT” Now?

5

Increase in

Processing Power

& Cheaper Storage

Explosion

of data –

Big Data Ease of Analyzing Data

Big Data Intel Inside Pentium

Intel Inside Pentium 4

Intel Inside Core Duo 2

Intel Inside Core Quad 2

Intel Inside Core i5

Oracle

Weka The University of Waikato

SAS

IBMSPSS Software

Rapidminer

IBM WatsonKNIME

Revolution Analytics

What is BIG DATA?

6

VolumeScale of Data

Variety Different Forms of Data

VelocityAnalysis of Streaming Data

VeracityUncertainty of Data

The FOUR V’s of Big

Data

Analytics Applications

Financial Industry

Telco Consultancy

Healthcare RetailTransportation

& Logistics

7

Foundation Courses

Analytics Framework &

Business Context

Data Analytics Lab

Elective Courses

Customer Analytics

Operations Analytics

Big Data: Tools & Techniques *(new)

Visual Analytics

Text Analytics

Social Analytics

Applied Machine Learning *(new)

Predictive Analytics using Simulation

*(new)

Hands-on & Industry Linkage

Internship/ Capstone Project

Monthly industry seminars

General

Management

and IT &

Project

Management

courses

Full time : 1 year

Part time : 2 years

Introduction to

Statistics

Introduction to R

Programming

MITB (Analytics) Curriculum

9

B. Analytics

Technology &

Applications

C. Information Technology

Management

D. General Management

for Technology &

Operations

E. Internship / Capstone

Project

B.1 Analytics Framework &

Business Context

B.2 Data Analytics Lab

B.3 Customer Analytics &

Applications

B.4 Operations Analytics &

Applications

B.5 Big Data: Tools &

Techniques

B.6 Visual Analytics &

Applications

B.7 Text Analytics &

Applications

B.8 Social Analytics &

Applications

B.9 Applied Machine

Learning

B.10 Predictive Analytics

using Simulation

C.1* Innovation

Management

C.2 Spreadsheet Modeling

for Technology &

Operations Decisions

C.3 IT Project & Vendor

Management

C.4 Global Sourcing of

Technology &

Processes

D.1A* Financial Accounting

D.1C* Management

Accounting for T&O

Managers

D.2 Strategy & Organisation

D.3 Finance for T&O

Managers

D.4* HRM for Technology &

Operations Managers

E.1 Internship

• Internship Job description

definition

• Resume writing,

internship application &

interviews

• Industry attachment

E.2 Capstone Project

• Project definition,

development & critique

workshops

• Industry expert seminars

& company site visits

• Project Delivery

Equip with innovation, IT and project

management skills

The Curriculum in a Nutshell

10

B. Analytics

Technology &

Applications

C. Information Technology

Management

D. General Management

for Technology &

Operations

E. Internship / Capstone

Project

B.1 Analytics Framework &

Business Context

B.2 Data Analytics Lab

B.3 Customer Analytics &

Applications

B.4 Operations Analytics &

Applications

B.5 Big Data: Tools &

Techniques

B.6 Visual Analytics &

Applications

B.7 Text Analytics &

Applications

B.8 Social Analytics &

Applications

B.9 Applied Machine

Learning

B.10 Predictive Analytics

using Simulation

C.1* Innovation

Management

C.2 Spreadsheet Modeling

for Technology &

Operations Decisions

C.3 IT Project & Vendor

Management

C.4 Global Sourcing of

Technology &

Processes

D.1A* Financial Accounting

D.1C* Management

Accounting for T&O

Managers

D.2 Strategy & Organisation

D.3 Finance for T&O

Managers

D.4* HRM for Technology &

Operations Managers

E.1 Internship

• Internship Job description

definition

• Resume writing,

internship application &

interviews

• Industry attachment

E.2 Capstone Project

• Project definition,

development & critique

workshops

• Industry expert seminars

& company site visits

• Project Delivery

The Curriculum in a Nutshell

Develop business management skills

11

B. Analytics

Technology &

Applications

C. Information Technology

Management

D. General Management

for Technology &

Operations

E. Internship / Capstone

Project

B.1 Analytics Framework &

Business Context

B.2 Data Analytics Lab

B.3 Customer Analytics &

Applications

B.4 Operations Analytics &

Applications

B.5 Big Data: Tools &

Techniques

B.6 Visual Analytics &

Applications

B.7 Text Analytics &

Applications

B.8 Social Analytics &

Applications

B.9 Applied Machine

Learning

B.10 Predictive Analytics

using Simulation

C.1* Innovation

Management

C.2 Spreadsheet Modeling

for Technology &

Operations Decisions

C.3 IT Project & Vendor

Management

C.4 Global Sourcing of

Technology &

Processes

D.1A* Financial Accounting

D.1C* Management

Accounting for T&O

Managers

D.2 Strategy & Organisation

D.3 Finance for T&O

Managers

D.4* HRM for Technology &

Operations Managers

E.1 Internship

• Internship Job description

definition

• Resume writing,

internship application &

interviews

• Industry attachment

E.2 Capstone Project

• Project definition,

development & critique

workshops

• Industry expert seminars

& company site visits

• Project Delivery

The Curriculum in a Nutshell

Acquire hands-on industry experience, with internship opportunities for full-time

students.

MITB (Analytics) – At a Glance

First Master Program in Analytics in Asia

Launched in Jan 2011

10th intake (Aug 2016)

Our case won TUN teaching innovation award 2013

Our simulation games shortlisted for Wharton-QS Stars Reimagine Education Awards 2015

Largest ecosystem in Data & Decision Analytics related research

Wide selection of internship opportunity

Summary

• Benefits for commuters:– With real-time commuters data, model developed

will be able to give commuters a good gauge of the average waiting time at the train stations.

– New or existing mobile applications can be developed to tap into this useful information.

• Benefits for train operators:– The simulation model can be used as a test bed

to test various scenarios by varying some operational conditions like:• Train capacity (new models or add seats)

• Inter-station travelling time (change speed of trains)