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2018/19 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 View Timetable

Year running 2018/19

Pre-requisite qualifications

A-Level Mathematics or Statistics Grade B

Pre-requisites

LUBS1530Business Analytics 1

Co-requisites

LUBS2920Advanced Analytical Methods

This module is mutually exclusive with

LUBS2935Intermediate Business Analytics
LUBS3205Advanced 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 typeNumberLength hoursStudent hours
Lecture221.0022.00
Tutorial181.0018.00
Private study hours160.00
Total Contact hours40.00
Total hours (100hr per 10 credits)200.00

Private study

Private study
3 hours reading per lecture = 66 hours
3 hours preparation per tutorial = 54 hours
Assessed coursework = 40 hours
Total private study = 160 hours

Opportunities for Formative Feedback

Student progress will be monitored principally by tutorial performance. Selected tutorial assignments will be submitted in advance and marked to provide feedback on student progress.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
Report3500 words100.00
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 website

Last updated: 12/12/2018 10:48:53

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