Module BUSI4AY15: Business Analytics

Department: Management and Marketing

BUSI4AY15: Business Analytics

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To equip students with an in-depth understanding of key principles of the decision making process in business and management.
• To develop students; skills in undertaking data analytics (descriptive and predictive).
• To provide real experience in analysing real-world problems.
• To enable students to be able to inspire business actions and influence business leaders using powerful data visualisations and storytelling.

Content

• Mastery of descriptive techniques e.g. data visualisation, data analysis, and descriptive statistics.
• Basic concepts in predictive analytics techniques.

Learning Outcomes

• By the end of the module students should:
• Understand the role that data plays in organisations and the technical infrastructure, governance and data management policies, practices and culture that supports ethical use of data.
• Have in-depth knowledge of descriptive analytics techniques and be able to apply them critically to management problems.
• Have an understanding of the applicability and limitations of descriptive and predictive analytics techniques.
• Grasp the principles of data storytelling and how to use narratives to present data insights effectively.

• By the end of the module students should be able to:
• Confidently use appropriate computer software to manipulate and analyse data.
• Formulate a data science project / problem from business problem or context.
• Be able to use data, data visualisations and data story-telling to create compelling narratives for driving evidence-based business decisions.

• Effective verbal communication
• Planning, organising and time-management
• Problem solving and analysis
• Interpreting and using data
• Data visualisation and storytelling

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• The module is taught on a 10 x 2 hour lecture and 4 x 1 workshop basis.
• Lectures and Workshop sessions will cover both theoretical content and practice-based demonstrations using computer software. During these sessions, students will gain foundational knowledge in descriptive, predictive and prescriptive analytics and understand the role of data in organisations.
• Workshop sessions will involve students working in groups on case studies, focusing on performing the data analysis, building and executing the analytical models and making inferences based upon the results. Students are expected to have engaged with face to face lectures before attending the workshops.
• The summative assessment comprises a single video presentation. This assessment emphasizes the practical nature of business analytics and data science, requiring students to undertake their analysis independently with the help of computer software.
• The formative assessment consist of classroom-based exercises involving individual and group analytical work on a business problem.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

For the formative assessment, the student will receive individualised feedback on the suitability of their chosen business problem and data set.

■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.