Programme And Module Handbook
Course Details in 2024/25 Session

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Module Title LH Business Analytics
SchoolBirmingham Business School
Department Accounting
Module Code 07 34272
Module Lead Dan Herbert
Level Honours Level
Credits 20
Semester Semester 2
Restrictions None
Contact Hours Lecture-30 hours
Project supervision-30 hours
Guided independent study-140 hours
Total: 200 hours
Description The module will introduce core concepts including but not limited to business intelligence, predictive analytic techniques, visualisation, big data and machine learning.
This module develops students’ familiarity with practical aspects of business analytics, such as types of data, sources, extraction, cleaning, manipulation and visualisation. It provides exposure to real-world business analytics applications and challenges.
Students will be introduced to core concepts in analytics and the issues relating to the deployment of analytics projects in organsiations. They will also consider the social, ethical and privacy issues arising from the use of analytics in organisations as well as the opportunities that flow from developments such as the use of open data.
Learning Outcomes By the end of the module students should be able to:
  • Critically evaluate the potential of analytic techniques in addressing business issues
  • Discuss ethical and privacy issues as they relate to analytics, machine learning and AI
  • Critically evaluate the role of big data in business
  • Select, evaluate and apply data extraction techniques to real-world datasets.
  • Critically appraise techniques used for data cleaning, manipulation, and analysis and apply these techniques to real-world datasets using industry standard software tools.
  • Select and implement techniques for data visualisation and apply this to real-world datasets.
Assessment 34272-01 : Coursework - Analytics Task : Coursework (75%)
34272-02 : Group Presentation : Presentation (25%)
Assessment Methods & Exceptions Assessments:
Individual analytics task (eg data visualisation or predictive analytics work) with critical commentary 2,000 words (75%)
Group case study video presentation equivalent to 1000 words (25%)

Reading List