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:

 

S/N

Topics and concepts

Sample Data and Problem Sets

Software Tools

1

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)

 

 

2

Solution process flow to solve data analytics problems

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

 

 

3

Data Manipulation and Visualization

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

4

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

5

Social Network Analysis

  • Extract information and interpretation
  • Gephi

6

Text Mining

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

7

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
Fees

$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.

Instructors for Workshop:

 

Dr. Michelle Cheong

Associate Professor of Information Systems

Associate Dean, SIS Post-Graduate Professional Education

Singapore Management University

 

Prior to joining SMU, Dr. Michelle Cheong had 8 years of industry experience leading teams to develop complex IT systems which were implemented enterprise-wide covering business functions from sales to engineering, inventory management, planning, production, and distribution. She joined SMU in 2005 where she teaches the Business Modeling with Spreadsheets course at the undergraduate and master levels. She is the co-author of a book on the same topic. Michelle was instrumental in designing and launching the Master of IT in Business (Analytics) programme in January 2011, which is the first Analytics master’s programme in Asia. The programme remains the leading one of its kind today. She also designed and teaches the Operations Analytics course in the MITB (Analytics) programme, and several executive courses in Data Analytics for other programmes including Master of Science in Communication Management, IE-SMU MBA, and Master of Science in Innovation.

 

Dr. Kam Tin Seong

Associate Professor of Information Systems

Singapore Management University

 

Dr. Kam Tin Seong is Associate Professor of Information Systems (Practice) at the School of Information Systems, Singapore Management University. He has more than twenty years of experience in both the analytics industry as well as academia. Assoc Prof Kam is active in consulting work as well as executive training in data visualization, data analytics, customer analytics, GIS and geospatial analytics for government agencies and companies. Some organisations that he consulted or conducted training programmes for include P&G, Citibank, Standard Chartered Bank, DBS, OCBC, UOB, Alexandra Health Institute, Jurong Health Services, East Health Alliance, Health Promotion Board, Ministry of Home Affairs, Ministry of Finance, Ministry of Manpower, Urban Redevelopment Authority (URA), Singapore Land Authority (SLA), Land Transport Authority (LTA), Jurong Town Corporation (JTC), National Environmental Agency (NEA), Ministry of Manpower, Ministry of National Development, National Library Board, Central Provident Fund Board (CPF), United Nations Centre for Regional Development, Asia Development Bank, Japan-Indonesia Forum (JIF), PT. Freeport, Brunei Shell Petroleum, UNOCAL Thailand, and ConocoPhillips, Indonesia.

 

Dr. Jiang Jing

Associate Professor of Information Systems

Singapore Management University

 

Dr. Jiang Jing is an Associate Professor of Information Systems at the Singapore Management University. Her general research areas are in text mining and natural language processing. Her recent work focuses on topic modeling, information extraction and social media text mining. She currently serves on the editorial board of Computational Linguistics and Information Processing & Management. Her work has been regularly published in top journals of natural language processing and data mining.