Topic 1 Introducing analytical decisions

1. Define the purpose of business analytics and explain how their use may provide value to organisations

2. Distinguish business intelligence from business analytics regarding focus of the eight analytical steps

3. Describe using an applied example the four analytics components

4. Illustrate with examples four business requirements for integrating business analytics

Topic 2 Numeracy and data modelling

1. Define statistics and explain their purpose in relation to numbers

2. Explain what is meant by a hypothesis and how this concept may be used in business analytics

3. Distinguish between three basic forms of numerical data and provide an example of how each may be summarised using statistics

4. Give real-world examples of positive, negative and zero correlations and explain whether these may or may not represent cause-effect relationships

Topic 3 Data mining

1. Define data mining and explain with an example how this integrates artificial intelligence, machine learning, statistics and databases

2. Explain the data mining process from available data to scoring using a real world example

3. Distinguish between supervised learning and unsupervised learning with respect to fundamental approaches

4. Describe and evaluate a method used to support supervised learning and a method used to support unsupervised learning

Topic 4 Forecasting, optimisation and simulation

1. Describe the purpose of forecasting using examples for three distinct approaches

2. Define optimisation and provide an example of the technique's use in operations

3. Define simulation and provide an example of the technique's use in operations

4. Explain with an example how data may be used to support a holistic approach to a complete operational system