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Unit Summary

Unit type

UG Coursework Unit

Credit points

12

Unit aim

Provides students with the necessary knowledge and skills to effectively use business analytics to support decision making in the context of ‘big data’ as a strategic resource. As a ‘data-driven’ unit, students will be exposed to a variety of analytical techniques using software applications.

Unit content

Topic 1: Introduction to business analytics

Topic 2: Data visualisation

Topic 3: Descriptive numerical measures

Topic 4: Simple linear regression

Topic 5: Multiple linear regression - Part I

Topic 6: Multiple linear regression - Part II

Topic 7: Business Forecasting - Part I

Topic 8: Business Forecasting - Part II

Topic 9: Model Building - Part I

Topic 10: Model Building - Part II 

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:
1 Appraise the role of data analytics and implications of big data in helping organisations identify new opportunities and turn big data into a strategic resource.
2 Identify patterns and trends for transformation of big data into meaningful information for use to gain competitive advantage.
3 Apply statistical techniques using industry software to analyse relationships in the data for forecasting and evaluation purposes.
4 Evaluate and communicate results of analysis in a framework for translating data analysis into decision-making outcomes in a variety of business settings.

On completion of this unit, students should be able to:

  1. Appraise the role of data analytics and implications of big data in helping organisations identify new opportunities and turn big data into a strategic resource.
  2. Identify patterns and trends for transformation of big data into meaningful information for use to gain competitive advantage.
  3. Apply statistical techniques using industry software to analyse relationships in the data for forecasting and evaluation purposes.
  4. Evaluate and communicate results of analysis in a framework for translating data analysis into decision-making outcomes in a variety of business settings.

Prescribed texts

  • No prescribed texts.
Prescribed texts may change in future teaching periods.