2025/26 Undergraduate Module Catalogue

LUBS3012 Data Analytics for Business

20 Credits Class Size: 100

Module manager: Xingjie Wei
Email: x.wei1@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2025/26

This module is approved as a discovery module

Module summary

This module will expand your understanding of how businesses and other organisations use data analytics to support a data-driven approach to management decision making. The topics covered include data management, business applications of data analytics, and the strategic requirements for effective analytics.

Objectives

The objective of this module is to increase students' understanding of how businesses and other organisations use data analytics to support a data-driven approach to management decision making.

Learning outcomes

Upon completion of this module, students will be able to:
1. Critically discuss the fundamentals of business analytics and data management concepts
2.Understand the principle of data analytics business applications
3. Determine and evaluate the strategic prerequisites for effective analytics.
4. Investigate unstructured business problems in order to identify the critical factors involved using data analytics business applications
5. Interpret and critically evaluate data analysis results in unstructured business problems.

Syllabus

Indicative content:
1. The foundations of business analytics
2. Data understanding and architecture
3. Data preparation
4. Data Modelling and predictive analytics: classification, regression and clustering
5. Model performance evaluation
6. Deployment

Teaching Methods

Delivery type Number Length hours Student hours
Lecture 11 1 11
Practical 10 1.5 15
Private study hours 174
Total Contact hours 26
Total hours (100hr per 10 credits) 200

Private study

Post-lecture reading
Seminar handout reading and preparation
Coursework revision

Opportunities for Formative Feedback

In each lecture, there will be about 5 to 10 mins for students to ask questions about the coursework and receive feedback from teaching staffs. In each practical sessions for each week, there will be interactive practical tasks and feedback will be available to students so they can improve week by week. Besides that, there will be ‘mini-sessions’ where students will have individual time to show the teaching staffs part of their on-going coursework report / programme / data processing, and teaching staffs will provide formative feedback (verbal or written), so students will have the opportunity to improve their work and coursework report before final submission.

Methods of Assessment

Coursework
Assessment type Notes % of formal assessment
Report Max 4,000 word report on utilising data analytics methods on a specific dataset. 100
Total percentage (Assessment Coursework) 100

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading List

There is no reading list for this module

Last updated: 30/04/2025

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