Data analytics have been touted as the most important technology which will bring organizations to their next frontier.

Many success stories have been shared on how data analytics can help organizations make better decisions, including understanding their customers better, predicting outcomes, understanding public sentiments on the social media, and optimizing resources to achieve the best results.


Managers who are leading their organizations have to play the lead role in shaping the direction and planning the strategies on who, what, when, where and how should data analytics be applied in the different parts of the organization.


The proposed training is designed for managers covering several topics in the Data Analytics area. The training will be conducted by the senior faculty members from the School of Information Systems, who are experts in their respective areas.



The topics covered will include:



Topics and concepts

Sample Data and Problem Sets

Software Tools


Quick overview of Data Analytics

  • Demystifying Data Analytics
  • Data Analytics Methods: Statistical Learning, Data Mining & machine Learning
  • Big Data (mention only, point to relevant references)




Solution process flow to solve data analytics problems

  • Data Analytics Lifecycle
  • Data Analytics Technologies: Commercial off-the-shelf (COTS) vs open source




Data Manipulation and Visualization

  • Data exploration
  • Data cleaning and manipulation
  • Data merging, joining
  • Data visualization
  • Geospace
  • MyTransport.SG Data Mall
  • Tableau 10


Data Analytics Techniques

  • Supervised learning (1 hands-on + mention a few)
  • Unsupervised learning (1 hands-on + mention a few)
  • Pros and cons of each technique
  • Select the best technique
  • Train, test and validate model
  • Results assessment and interpretation
  • Rapid Miner


Social Network Analysis

  • Extract information and interpretation
  • Gephi


Text Mining

  • Text pre-processing
  • Text classification
  • Text clustering (including topic modelling)
  • Sentiment analysis
  • Forums, blogs, public Facebook, or AirBnB
  • Rapid Miner


Operations – Optimization

  • Optimization theory
  • LP, IP, MIP, BIP
  • Model formulation
  • Solver definition
  • Heuristic algorithm
  • Police patrol problem
  • Nurse scheduling problem
  • MS Excel 2013 with Solver Add-in installed




Duration 2 days
Dates 17-18 August 2017

$1600 per pax (excluding GST)

The cost of training will include the following:

  • 7.5-hours/day (excluding lunch and break times) training covering the topics listed above.
  • Pre-reading materials in soft copy
  • Training materials in soft copy
  • List of software to be installed in the laptop PCs for the training. SMU does not provide the laptops and software for the training purpose.