An Interactive 5-Day Training Course
Advanced Data Analysis Techniques
Modelling, Simulation, Optimisation and Predictive Analytics using Microsoft Excel
Course Overview
The statistical analysis of numerical information is proven to be a powerful tool, providing businesses with everyday insight into matters like corporate finance, manufacturing processes, service provision and product quality control.
However, the advent of the Internet of Things, the consequential growth in Big Data, and the ever-increasing business requirements to model and predict, mean that many of the analytical opportunities and needs of a modern, high performing company cannot be met using conventional data analysis methods alone.
More and more companies are wrestling with complex modelling and simulation problems, addressing matters like trying to optimize production systems, to maximize performance efficiency, to minimize operating costs, to combat risk, to detect fraud and to predict future behavior and outcomes.
This Advanced Data Analysis Techniques training course is 100% computer-based and shows by example how to use Microsoft Excel to solve a series of complex and realistic business problems. The problems are drawn from the widest possible range of applications – from robotics to refining, from supply chain logistics to production optimization and from financial risk management to the efficient provision of healthcare. All the problems are different and all convey carefully designed learning objectives.
Delegates will learn how to code and simulate realistic problems and then how to use these simulations to understand system operation, to optimize performance, and to predict future behavior. The training course is intended for people who are experienced in conventional data analysis techniques, and who now want to become specialist in the modelling and simulation of complex business activities.
Training Objectives
This training course aims to provide those involved in monitoring, managing and controlling complex business processes with the understanding and practical capabilities needed to convert data into meaningful information via a range of very powerful modelling, simulation and predictive analytical methods.
The specific objectives of this Advanced Data Analysis Techniques training course are as follows:
- To teach delegates how to solve a wide range of complex business problems which require modelling, simulation and predictive analytical approaches
- To show delegates precisely how to implement a range of modelling, simulation and predictive analytical methods using Microsoft Excel 2016 (or 365)
- To provide delegates with both a conceptual understanding and practical experience of advanced data analysis methods including: Bayesian models, conventional and genetic optimization methods, Monte Carlo models, Markov models, What If analysis, Time Series models, Linear Programming, and more
- To engage delegates for the entire 3 days in the exploration and use of modelling and simulation methods within Microsoft Excel, to develop complete solutions to the 8 totally realistic business problems that are presented
- To enable delegates to make the shift from intuition-based to information-based decision making in complex situations, hence enabling them to enhance their forecasting and future behavior predictions, increase their proficiency in risk assessment and risk-informed decision making, and to exploit to a much greater extent the wealth of information contained in Big Data
- To provide a clear understanding of why the best companies in the world see modelling, simulation and predictive analytics as being essential to delivering the right quality products and optimized services at the lowest possible costs
Who should Attend?
This GLOMACS Advanced Data Analysis Techniques training course has been designed for professionals whose jobs involve the manipulation, representation, interpretation and/or analysis of data. This training course involves extensive modelling and analysis using Excel 2010 (or higher) and therefore delegates must not only be numerate, but must enjoy detailed working with numerical data to solve complex problems.
Full familiarity with Microsoft Excel (version 2007 or higher), and the ability to analyze data using common statistical methods, are fundamental prerequisites for attendance on this Advanced Data Analysis Techniques training course.
About Saudi Glomacs
At Saudi GLOMACS, we specialize in delivering world-class training courses in Saudi Arabia and across various international locations. Our training courses are tailored to meet the unique demands of Saudi Vision 2030 and the Human Capability Development Program, focusing on empowering Saudi citizens and enhancing workforce skills. We offer diverse courses spanning leadership, management, engineering, and technical disciplines to cultivate expertise and drive professional growth. Our flexible learning options—whether in-person, online, or in-house—ensure accessibility and convenience for individuals and organizations alike.
With over 30+ years of experience through the GLOMACS global network, we are committed to delivering innovative, results-driven training solutions. Our expert instructors combine industry knowledge with dynamic teaching methods, fostering practical skill development and long-term career success. By choosing Saudi GLOMACS, you're investing in personal excellence and contributing to the Kingdom’s sustainable economic growth and vision-driven transformation.
Training Outline
DAY 1: Linear Programming
- Introduction to Optimisation; Multi‐variate Optimisation Problems; Determining the Objective Function; Constraints to Problems; Sign Restrictions; The ‘feasibility region’; Graphical Representation; Implementation using Solver in Excel
- Using Linear Programming to Solve Production and Supply Chain / Logistics Problems, such as optimising the products from a refinery, and minimising the manufacturing and delivery costs for a complex supply chain (with and without batch manufacturing, and with and without warehousing)
DAY 2: Newtonian and Genetic Optimisation Methods
- Linear and Non‐linear Optimisation Problems; Stochastic Search Strategies; Introduction to Genetic Algorithms; Biological Origins; Shortcomings of Newton‐type optimisers; How to Apply Genetic Algorithms; Encoding; Selection; Recombination; Mutation; How to Parallelise; Implementation using Solver in Excel
- How to Solve a range of Optimisation Problems, Culminating in the classic ‘travelling salesman problem’ by optimising the motion trajectory of a large manufacturing robot, both with and without forced constraints
DAY 3: Scenario Analysis
- Introduction to Scenario Analysis; A What‐If example in Excel; Types of What‐If analysis; Performing manual what‐if analysis in Excel; One Variable Data Tables; Two‐variable data tables
- Using Scenario Manager in Excel; Using scenario analysis to predict business expenses and revenues for an uncertain future
DAY 4: Markov Models
- Understanding Risk; Introduction to Markov Models; 5 Steps for Developing Markov Models; Manipulating Arrays and Matrices inside Excel; Constructing the Markov Model; Analysing the Model; Roll Back and Sensitivity Analysis; First‐order Monte Carlo; Second‐order Monte Carlo
- Decision Trees and Markov Models; Simplifying Tree Structures; Explicitly Accounting for Timing of Events
- Using Markov Chains to simulate an insurance no claims discount scheme, and Modelling the Outcomes of a Healthcare System
DAY 5: Monte Carlo Simulation
- Introduction to Monte Carlo Simulation; Monte Carlo building blocks in Excel; Using the RAND() function; Learning to model the problem; Building worksheet‐based simulations; Simple problems; How many iterations are enough?; Defining complex problems; Modelling the variables; Analysing the data; Freezing the model; Manual recalculation; "Paste Values" function; Basic statistical functions; PERCENTILE() function
- Monte Carlo Simulation solutions to problems of traffic flow in a city, dealing with uncertainty in the sale of product, predicting market growth and assessing risk in currency exchange rates
Certificates
- On successful completion of this training course, GLOMACS Certificate will be awarded to the delegates
- Continuing Professional Education credits (CPE) : In accordance with the standards of the National Registry of CPE Sponsor, one CPE credit is granted per 50 minutes of attendance
Accreditation
GLOMACS is registered with NASBA as a sponsor of Continuing Professional Education (CPE) on the National Registry of CPE Sponsors. NASBA have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.learningmarket.org.
All Training Seminars delivered by GLOMACS by default are eligible for CPE Credit.
Providers and Associations
Sessions in international locations
Online Sessions
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