Business Analytics

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This module aims to:

  • develop a critical awareness of the range of tools being marketed under the label "Decision Support" or more generally "Business Intelligence" (BI);
  • provide an understanding of the key algorithms and techniques which are embodied in Business Intelligence solutions.

After completing this module participants will be able to:

  • understand the way in which classical statistical techniques are applied in modern BI solutions;
  • discuss the potential application of BI tools to various types of business problem-solving and appreciate their limitations;
  • describe the range of computer based approaches to representation and reasoning with formal and quantitative knowledge;
  • understand the role of end users and analysts in BI, and the important differences between decision support and decision-making.

Indicative topics:

  • Modelling the mind: deduction, induction, machine learning and neural networks;
  • Knowledge-based tools: expert systems, case-based reasoning, DSS;
  • Quantitative methods for data analysis and knowledge extraction: classification and regression, clustering, association rule, Bayesian approaches, belief networks;
  • Modelling, simulation, optimisation and uncertainty;
  • BI applications: data mining, knowledge management, decision analysis, text mining, etc.