| Event Profile | |
| Class/ Online | Classroom |
| Date | November 27, 2025 |
| Time | 9.00am to 5.00pm |
| Venue | Holiday Inn Atrium Singapore (Halal Certified) 317 Outram Road Singapore 169075 |
| Fee | 9% GST will apply SGD 550.003 & above: SGD520.00 each For Member SGD 522.5 3 & above: SGD494 each |
| Note | Two tea breaks and buffet lunch will be served. Limited complimentary car parking coupons are available upon request. |
| Other Date(s) | 1) Aug 25, 2025 |
| Trainer | |
| Activity | |
| You may reach us via T: 6204 6214 E: info@ccisg.com Alternatively, you may send below details to register Contact Person Company (optional), Name, Job Title, Mailing Address, Tel, Email Participant(s) Name, Job Title, Email | |
Optimization isn’t just beneficial - it's essential for achieving business success.
This hands-on course provides a comprehensive exploration of how data can be practically applied to identify, analyze, and solve real-world business problems.
Participants will begin by understanding the foundational role of data in business decision-making. They will learn to use essential tools such as pivot tables, charts, and descriptive statistics to uncover insights and drive effective problem-solving. The course will also introduce comparison and trend analysis techniques, equipping learners to make smarter, data-driven decisions.
Building on this foundation, participants will explore advanced “What-If” analysis through tools like Goal Seek and Scenario Manager, enabling them to model different business scenarios and assess potential outcomes. They’ll also develop skills in creating data tables, performing sensitivity analysis, and setting realistic, data-backed targets.
The course then progresses to optimization techniques using Solver, where learners will discover how to maximize profits, minimize costs, and allocate resources effectively - covering applications like network optimization and portfolio management.
Finally, participants will enter the predictive realm with Markov Chain models. They’ll learn how to construct transition matrices, generate random numbers, and apply Markov Simulation to forecast future business states with greater accuracy.
This hands-on course provides a comprehensive exploration of how data can be practically applied to identify, analyze, and solve real-world business problems.
Participants will begin by understanding the foundational role of data in business decision-making. They will learn to use essential tools such as pivot tables, charts, and descriptive statistics to uncover insights and drive effective problem-solving. The course will also introduce comparison and trend analysis techniques, equipping learners to make smarter, data-driven decisions.
Building on this foundation, participants will explore advanced “What-If” analysis through tools like Goal Seek and Scenario Manager, enabling them to model different business scenarios and assess potential outcomes. They’ll also develop skills in creating data tables, performing sensitivity analysis, and setting realistic, data-backed targets.
The course then progresses to optimization techniques using Solver, where learners will discover how to maximize profits, minimize costs, and allocate resources effectively - covering applications like network optimization and portfolio management.
Finally, participants will enter the predictive realm with Markov Chain models. They’ll learn how to construct transition matrices, generate random numbers, and apply Markov Simulation to forecast future business states with greater accuracy.
Objective
Upon completing the course, learners will be able to:
- Confidently use pivot tables and charts, choose suitable visualization tools, and enhance data presentation for effective and impactful communication.
- Apply structured analytical techniques to interpret business data, gaining deeper insights into market trends, customer behavior, and operational performance.
- Perform regression analysis and predictive modeling to identify key variables and trends, supporting accurate business forecasting.
- Develop prescriptive strategies and conduct forecasting using advanced methods to project and plan for future business scenarios.
Outline
1. Digital Analytics Framework
2. Data Analytics Techniques
3. Descriptive Analytics and Prediction
4. Prescriptive Analytics and Forecasting
- The significance of data in driving business success
- Different levels of data analytics
- Utilizing pivot tables and charts effectively
- Selecting the most appropriate chart types
- Best practices for limiting color choices to enhance clarity
2. Data Analytics Techniques
- The four-step analytics framework
- Comparison and ranking analysis
- Trend identification and gap analysis
- Pareto principle and contribution analysis
- Cohort analysis for segment insights
3. Descriptive Analytics and Prediction
- Navigating the Data Analytics tab
- Conducting descriptive analytics and comparative studies
- Understanding regression analysis, coefficients, and variables
- Selecting the best-fit trend line for data modeling
- Making predictions using model formulas
4. Prescriptive Analytics and Forecasting
- Prescriptive analytics and optimization strategies
- Variable selection for actionable recommendations
- Applying moving averages and time series analysis
- Techniques for forecasting future trends
Who should attend
This course is designed for professionals who already have a strong working knowledge of Microsoft Excel and are ready to take their skills to the next level with practical data analytics techniques. It is not suitable for Excel beginners.
- Business strategists who want to incorporate data analytics into their decision-making processes.
- Data analysts focused on enhancing their analytical methods and improving reporting capabilities.
- Marketing professionals aiming to utilize data insights for more effective targeting strategies.
- Operations managers exploring data-driven approaches to optimize processes.
- Financial analysts seeking advanced forecasting techniques to support financial planning.
Testimonial
"With concise and clear delivery, the trainer effectively covered predictive and prescriptive forecasting using large data sets."
"Patient and thorough, the trainer ensures everyone is on track, making everything in the workshop highly useful."
"The trainer is excellent at simplifying complex statistical concepts and emphasising practical application, making everything in the workshop highly useful."
"Highly recommended for beginners to take up for learning data analytics."
"Patient and thorough, the trainer ensures everyone is on track, making everything in the workshop highly useful."
"The trainer is excellent at simplifying complex statistical concepts and emphasising practical application, making everything in the workshop highly useful."
"Highly recommended for beginners to take up for learning data analytics."
Dwight Nuwan Fonseka's Profile
Head Data Analyst | Data Governance & AI | CAIP | CDSP | ACLP
Dwight Fonseka is a seasoned data analytics professional with over a decade of experience in big data, predictive modeling, and AI. Holding a Master’s in Education (NTU), a degree in Biotechnology (NUS). He is a Certified AI Practitioner (CAIP), Certified Data Science Practitioner (CDSP), and ACLP-certified trainer with extensive experience delivering data-driven insights and practical applications across industries.
Dwight has held roles such as Senior Data Analyst and Data Governance Officer at Plano Pte Ltd, specializing in healthcare analytics and machine learning. As an adjunct trainer, he delivers practical courses in data visualization, data storytelling, deep learning, and AI business models, using tools like R, Python, Tableau, and RapidMiner.
Notable Topics Trained:
Dwight Fonseka is a seasoned data analytics professional with over a decade of experience in big data, predictive modeling, and AI. Holding a Master’s in Education (NTU), a degree in Biotechnology (NUS). He is a Certified AI Practitioner (CAIP), Certified Data Science Practitioner (CDSP), and ACLP-certified trainer with extensive experience delivering data-driven insights and practical applications across industries.
Dwight has held roles such as Senior Data Analyst and Data Governance Officer at Plano Pte Ltd, specializing in healthcare analytics and machine learning. As an adjunct trainer, he delivers practical courses in data visualization, data storytelling, deep learning, and AI business models, using tools like R, Python, Tableau, and RapidMiner.
Notable Topics Trained:
- Data Analytics & Visualization (R, Tableau, Excel)
- Machine & Deep Learning (RapidMiner, DeepCognition)
- Data Governance & AI Business Models
- Predictive Analytics & Data-Driven Decision-Making
