Applied analytical modelling has become prevalent in many industries and has developed in the mathematic al techniques used and the diversity of modelling tools and techniques. Applied analytical modelling is carried out by a data scientist utilising modelling data, model building and model reporting skills. The aim of this unit is to provide students with knowledge and analytical modelling skills using computers to discover and interpret meaningful patterns in data by creating computer models.
This unit introduces students to applied analytical models used in business to discover, interpret and communic ate meaningful patterns of data held in silos or data warehouses, and to derive knowledge to gain competitive advantage.
Organisations may apply analytical methods and models to predict/prescribe business outcomes and improve performance in diverse areas such as stock control, financial risk and fraud analysis. Analytical models use mathematic al algorithms and require extensive computation to process large amounts of data.
Among the topics included in this unit are: data preparation, fundamentals of applied analytical models and development of predictive or prescriptive models using a suitable algorithm, operating on a large data set.
As a result they will develop skills such as communic ation literacy, critical thinking, analysis, reasoning and interpretation which are crucial for gaining employment and developing academic competence.
By the end of this unit students will be able to:
LO1. Examine applied analytical modelling methods.
LO2. Prepare a large data set for use in an applied analytical model.
LO3. Demonstrate the use of an analytical model with a large data set.
LO4. Investigate improve ments to an applied analytical model.
