2020/21 Undergraduate Module Catalogue
LUBS2940 Business Analytics 2
20 creditsClass Size: 30
Module manager: Xingjie Wei
Email: X.Wei1@leeds.ac.uk
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2020/21
Pre-requisite qualifications
A-Level Mathematics or Statistics Grade BPre-requisites
| LUBS1530 | Business Analytics 1 |
Co-requisites
| LUBS2920 | Advanced Analytical Methods |
This module is mutually exclusive with
| LUBS2935 | Intermediate Business Analytics |
| LUBS3205 | Advanced Business Analytics |
This module is not approved as a discovery module
Module summary
This module will extend your knowledge about how businesses and other organisations use data analytics to support an evidence-based approach to management decision making. Topics covered include data management, business applications of data analytics, and the strategic and cultural requirements for effective analytics.Objectives
The module aims to extend the knowledge of students on how businesses and other organisations use data analytics to support an evidence-based approach to management decision making.Learning outcomes
Learning Outcomes - Knowledge/Application
Upon completion of this module students will be able to:
1. Discuss the foundations of business analytics
2. Apply concepts of data management
3. Use business applications of data analytics
4. Identify and discuss the strategic and cultural requirements for effective analytics
Learning Outcomes – Skills
Upon completion of this module students will be able to:
Subject specific
1. Research unstructured business problems with the ability to identify the critical factors involved
2. Apply statistical and other quantitative methods accurately to analyse unstructured business problems
3. Critically evaluate and interpret the results of data analysis in unstructured business problems
Transferable
1. Write and communicate effectively
Skills outcomes
Upon completion of this module students will be able to:
1 Research unstructured business problems with the ability to identify the critical factors involved
2 Apply statistical and other quantitative methods accurately to analyse unstructured business problems
3 Critically evaluate and interpret the results of data analysis in unstructured business problems
Syllabus
Indicative content:
1. The foundations of business analytics
2. Data architecture
3. Data silos and integrated data systems
4. Advanced data visualisation
5. Operations research
6. Performance analytics
7. Predictive analytics
8. Investment analytics
9. Retail/market analytics
10. Strategic and cultural requirements for effective analytics
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Workshop | 18 | 1.00 | 18.00 |
| Lecture | 22 | 1.00 | 22.00 |
| Private study hours | 160.00 | ||
| Total Contact hours | 40.00 | ||
| Total hours (100hr per 10 credits) | 200.00 | ||
Private study
This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.Opportunities for Formative Feedback
Your teaching methods could include a variety of delivery models, such as face-to-face teaching, live webinars, discussion boards and other interactive activities. There will be opportunities for formative feedback throughout the module.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Report | 3500 words | 100.00 |
| Total percentage (Assessment Coursework) | 100.00 | |
The resit for this module will be 100% by 3,500 word coursework.
Reading list
The reading list is available from the Library websiteLast updated: 10/08/2020 08:41:47
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