School of Infocomm (SOI)

Insights into Customer Trends Using Data Analytics

Little Skoolz, an educational technology platform can optimise marketing, improve efficiency, and deliver a superior learning experience. By leveraging Robotic Process Automation (RPA) and data analytics for smarter decision-making, users can focus on more productive tasks, gain a deeper customer understanding, and deliver a superior learning experience. Key features include: 

• Customer Profiles Automation: UiPath's RPA streamlines customer profile creation, freeing up Little Skoolz's team for strategy and innovation.
• Social Media Integration: Valuable insights from social media inform marketing efforts and understand parent preferences.
• Actionable Data Visualisation: Tableau transforms complex data into clear visuals, enabling data-driven decisions for marketing and operations.
   

Team Members:
Halimah Binte Mohd Nordin, Soh Shi Ting Jolin, Nur Mahirah Bte Sukairi, Samantha Ng Shi Yu

Supervisor:
Ms Mary Yeo 

Management Reporting System for Startups

This project streamlines management reporting for RP's Office of Entrepreneurial Development (OED) startups. It automates data collection, analysis, and reporting using Microsoft technologies:

• Automated Data Capture: SharePoint Lists and Forms automate data collection from startups, reducing manual entry and errors.
• Streamlined Analysis: Power Automate handles data processing, freeing up OED staff for more strategic initiatives.
• Interactive Dashboards: Power BI presents data visually, enabling better data-driven decisions for OED programs.
• Customizable Reports: Excel reports provide detailed information for stakeholders.

This automation improves admin efficiency, reduces errors, and empowers OED with valuable insights for supporting their affiliated startups.
 

Team Members:
Nur Bayyinah Bte Mahmood, Nur Shirin Bte Zainollah, Jose Thomas Akssa Mary, Eunice Tan Eng Eng

Supervisor:
Ms Tay Sok Kem 

Business Intelligence System

This project streamlines the monthly legal reporting of Overseas Chinese Banking Corporation (OCBC) by automating the ETL process (Extract, Transform, Load) using VBA macros and Power BI with the following benefits:

• Automated Data Pipeline: VBA macros handle data extraction, reducing manual effort and potential errors.
• Streamlined Reporting: Power BI automates report creation, saving time and ensuring consistency.
• Interactive Dashboards: Data visualisations empower legal professionals with clear insights for informed decision-making.
• Improved Business Intelligence: This automation enhances data analysis capabilities, significantly contributing to OCBC's business intelligence processes.
   

Team Members:
Nelly Ayumi Bte Ja'affar, Aryna Bte Ramlan, Muhammad Izhar B Abdul Malik, Alicia Tan Xin Yi

Supervisor:
Mr Henry Leong

Data Analytics on Accident Statistics to Improve Operational Safety

Main Aim of the Project: 

This project aims to find out the main causes of accidents and how to minimise the number of the occurrences across the United Kingdom. 

Prediction Model Solution: 

• For visualisation and predictive analysis purposes, data was analysed to identify trends and visualise on various charts and dashboards to gain insights on the accidents that occurred. 

• This project also aids in predicting the severity of future accidents and improve road safety with Supervised Machine Learning Algorithms performed on datasets collected and a Decision Tree Prediction Model to uncover significant causes of accidents.

• Data-driven suggestions were then proposed to boost road traffic safety.
   

Team Members: 
Nadya Allysha Zulkefli Kai Ling, Lee Bee Geok, Nurul Natasha Bte Mohamad Naim

Supervisor:
Ms Yong Yoke Fong

Data Analytics on Students' Feedback Survey and Performance

At present, data from feedback survey results as well as module results are manually managed, with staff spending long hours to consolidate and analyse them. 

Main Aim of the Project: 

• This project aims to develop a system which enables authorised staff to automate the process by allowing the results from modules and feedback surveys to be imported for analysis purposes.

• The system allows to imports student data to facilitate analysis.

• The consolidated results will, in turn, help improve the students' well-being.
   

Team Members: 
Loh Shi Hui Vanessa, Kok Wai Teng, Stephanie Leow Yu Hui, Kok Li Xian

Supervisor:
Mr Austin Chong

Effective Medical Stocking through Analytics

Partner Organisation: Ng Teng Fong General Hospital 

Main Aim of the Project: 

The project aims to reduce the man-hour spent on medicinal inventory management, reduce errors due to inaccurate setting of par level that can cause inventory shortage during critical times and reduce overstocking wastages for the staff in the different departments of a hospital. Staff workload can be reduced too. 

Final Solution: 

To do so, the following are performed and/or developed: 

• Analyse the past inventory trends using data analytics. 

• Forecast demand/predictive nature of drug usage. 

• Programme that is able to produce optimal par level numbers for a specific period based on input of the historical drug dispensing and usage data.
   

Team Members: 
Ng Min Yuan Jocelyn, Chevelle Tan Zi Ting, Yip Sheng Yue

Supervisor:
Mr Henry Leong

Car Value Data Analysis

Partner Organisation: Motorist PTE LTD 

Main Aim of the Project: 

This project aims to develop an application that can predict the future car value by entering certain information of a car. 

Expected Outcomes: 

• The app's data can aid the user in determining the vehicle's fair market value. 

• To aid in that, models are trained, followed by being employed to perform predictive future car value.

• The company may use the prediction to better advise customers on their vehicle's value. 

Team Members: 
Zheng Xiang Jun, Feng Zhi Xin

Supervisor:
Ms Jane Zhang

Data Analytics on Accident Statistics to Improve Operational Safety

Main Aim of the Project: 

Nearly 40,000 people lost their lives in car accidents in the United States every year.

• This project aims to help in reducing the number of deaths caused by car accidents through analysing different accident-related factors through charts, and hence to discover the existing accident patterns.

• Predictions are then made on accidents with major severity levels and its related factors to further avoid accidents under those conditions. Data cleansing was also done to ensure accuracy of the result. 
   

Team Members: 
Teo Jiaman, Soh Yanqing, Li Siying

Supervisor:
Mr. Florian Muljono

DataCo Supply Chain Data Analytics

DataCo Global needs help in their Business Decision Making. There is lack of useful reports to help the management team to identify the threats and opportunities in the company. There are no reports generated to help them understand the transactional data. 

It is very challenging for the management team to understand the downloaded data from the Excel file. 

Main Aim of the Project: 

The project aims to provide an analytic system that can read the data, interpret and derive useful information from the data, and provide insight about the company performances.

The system should generate useful and easy to read reports to help them make the right business decisions. 

Team Members: 
Ummi Haziyah Bte Mohamed Salim, Cheng Lai Yeng Iris, Emilyn Tin Ting Hui, Nadia Bte Haider

Supervisor:
Mr Peter Liew