The statistical analysis of numerical information is proven to be a powerful tool, providing everyday insight into matters like corporate finance, production processes and quality control. However, the advent of the Internet of Things, the consequential growth in Big Data, and the ever-increasing 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 statistical methods alone.
More and more companies are wrestling with complex modelling and simulation problems, addressing matters like trying to optimise production systems, to maximise performance efficiency, to minimise operating costs, to combat risk, to detect fraud and to predict future behaviour and outcomes.
This PetroKnowledge training course aims to provide those involved in analysing numerical data with the understanding and practical capabilities needed to convert data into meaningful information via the use of a range of very powerful modelling, simulation and predictive analytical methods. The specific objectives are as follows:
- To teach delegates how to solve a wide range of business problems which require modelling, simulation and predictive analytical approaches
- To show delegates how to implement a wide range of the more common modelling, simulation and predictive analytical methods using Microsoft Excel 2010 (or higher) and in particular the Solver tool
- To provide delegates with both a conceptual understanding and practical experience of a range of the more common modelling, simulation and predictive analytical techniques, including Bayesian models, conventional and genetic optimisation methods, Monte Carlo models, Markov models, What If analysis, Time Series models, Linear Programming, and more
- To give delegates the ability to recognize which modelling, simulation and predictive analysis methods are best suited to which types of problems
- To give delegates sufficient background and situation experience to be able to judge when an applied technique will likely lead to incorrect conclusions
- 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 optimised services at the lowest possible costs