Keele Badge

MAN-20149 - Module Specification
Keele Business School
Faculty of Humanities and Social Sciences

For academic year: 2025/26 Last Updated: 04 December 2025

MAN-20149 - Business Analytics
Coordinator: Muddasar Ghani Khwaja Room: N/A Tel: 07405194266
Lecture Time: See Timetable...
Level: Level 5
Credits: 15
Study Hours: 150
School Office: 01782 733094

Programme/Approved Electives for 2025/26

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2025/26

The use of data analytic techniques is now pervasive in organisations. All business functions have been impacted in some way. Marketing teams use data to identify and target key customer groups, Supply chain managers use data to identify efficiencies, finance teams use data to identify financial risks. In this module you will look at the data available to organisations, the issues it can be used to address and the techniques that can be used. You will use industry standard software tools to undertake your own analysis of data and develop your skills as a data communicator.

Aims
This module aims to introduce students to the techniques of analytics that can be deployed to understand common organisational issues. The module will introduce students to the sources of organisational data and the ways it can be stored, managed and summarised prior to use. The ethical, security and privacy issues linked to data will be addressed. Common analytic techniques using supervised and un-supervised learning methods will be introduced in theory. The module will then introduce students to the practical aspects of analytics focussing on the extraction of useful messages from data sets and the communication of these to organisational users.

Intended Learning Outcomes

Critically evaluate the use of analytics tools to inform business decision making
: 1,2
Select, apply and evaluate common analytics techniques and implement them using appropriate software tools
: 1,2
Communicate complex data to a range of users and to critically evaluate visual data communications
: 2

Study hours

12 x1 hour theory lectures
12 x1 hour practical workshops.
126 hours guided independent learning. Of this 30 hours will be used for the assignment task and a further 60 hours for the portfolio of analytics tasks. The remaining time will be used undertaking on-line self teaching based on materials available from Tableau and LinkedIn Learning. Students will be given guidance on the materials to use.

School Rules

None

Description of Module Assessment

1: Group Assessment weighted 50%
Analytics task portfolio and group presentation
In this assessment, you will work in groups of 4 to analyse a dataset from one of the provided sectors: Superstore, Restaurant, Retail Fashion, Electronics, Pharmacy, and Hotel All the above data sets are uploaded on KLE. Each group will receive or select a dataset and perform the same set of analytics tasks using Microsoft Excel and Power BI. The goal is to explore data, visualize patterns, identify trends, and provide actionable recommendations. Group presentation 10-15 minutes duration. Tasks to Complete: 1. Data Cleaning and Preparation (Excel) 2. Descriptive Statistics (Excel) 3. Trend Analysis (Excel) 4. Regional/Store/City Analysis (Excel / Power BI) 5. Category/Product/Service Analysis (Power BI) 6. Customer Satisfaction Analysis (Power BI) 7. Dashboard Creation (Power BI) 8. Insights and Recommendations (Portfolio + Presentation)

2: Assignment weighted 50%
Practical analytics project - 1000 word equivalent
Based on topics covered in Weeks 1–10, you are required to produce a 1000-word report on the hypothetical company, CresysX, an online retail company seeking opportunities for business improvement through both survey and sales data analysis. CresysX is an online retail company. Students must analyse the customer survey (n = 347) with SPSS (Part A) and compute & visualise website sales (Excel → Power BI) (Part B). Deliver a single Word report containing interpreted results, only relevant SPSS tables, screenshots of the Power BI dashboard and a URL to the published dashboard. Make sure to insert Power BI analysis files link in the report (.pbix).

The University undertakes a continuous review of its teaching and research provision to ensure programmes are of a high quality and changes may be made to modules where it is necessary and reasonable to do so. Please be aware that minor changes to modules, such as a change to an individual assessment, can occur up until enrolment, although we endeavour to give you as much notice as possible of any changes. Details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/legalgovernancecompliance/governance/actcharterstatutesordinancesandregulations/studenttermsconditions/

Last Updated: 04 December 2025