Business Analytics

Module title	Business Analytics
Module code	BEP2140
Academic year	2023/4
Credits	15
Module staff	Dr Eunice Oppon (Convenor)

Duration: Term	1	2	3
Duration: Weeks	0	11	0

Number students taking module (anticipated)	30

Module description

This module will explore the role of information and analytics in supporting the development of strategies, and the practical techniques managers can use to design effective information flows. You will be introduced to key concepts in data science for business, including fundamentals of data management, modelling, analysis and visualisation. You will consider how ‘design thinking’ can be used to effectively develop and deploy analytics systems within businesses, including the roles of descriptive, diagnostic, predictive and prescriptive systems. There are no pre-requisites but useful complementary modules to have taken in the first year include GEO1419 Introduction to Data Science.

Module aims - intentions of the module

Businesses are constantly faced with making decisions and managers are expected to make the right decisions to optimise their operations. The aim of this module is to equip students with the ability to use variety of quantitative tools in analysing data to aid decision making in business. Students will explore the use of the different quantitative tools for analysing data in realistic business situations including finance, marketing, operations and other areas of business. On completion of the module, students will develop competencies in the use of analytic software particularly Excel for data analysis and data visualisations to support effective decision making.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. Define business analytics (BA), related concepts and the importance of BA in a business environment
2. Conduct data analysis and construct data visualisations using basic and advanced excel functions to aid management decision making
3. Plan and execute quantitative analysis using descriptive, predictive and prescriptive analytical tools
4. Interpret the results of quantitative analysis and investigate potential issues

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

5. Critically evaluate the various factors which impact on effective management of analytics data when using descriptive, predictive and prescriptive analytical tools in a variety of business contexts
6. Effectively communicate findings to a variety of audiences

ILO: Personal and key skills

On successfully completing the module you will be able to...

7. Example computer literacy and analytical skills
8. Display an understanding for decision making analysis in a business context

Syllabus plan

Topics discussed on the module include (not exclusively):

Foundations of Business Analytics. Students will be introduced to basic concepts in business analytics including the use of basic data management and analytic software tools such as Excel
Descriptive Analytics. One important aim of business analytics, is to present meaningful and easy to understand information from the large data analysed. To achieve this, students will be introduced to data visualisation, descriptive statistics, probability and decision making under uncertainty
Predictive Analytics. Topics to be covered include times series and regression analysis, forecasting, use of spreadsheet to build and analyse data models
Prescriptive Analytics. Linear optimisation and its application
Making Decisions. Central idea of business analytics is to assist managers in decision making. Students will be introduced to the underlying philosophies, tools and techniques of decision analysis

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
22	128	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled learning and teaching activity	11	Lectures (11 x 1 hour)
Scheduled learning and teaching activity	11	Tutorials (11 x 1 hour)
Guided independent study	128	Reading, research and assessment preparation

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
In class quizzes and multiple choice exercises	During each class	1-8	Verbal in class

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
0	40	60

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Written exam	40	1 hour	1,5,8	Written
Practical exam	60	2 hours lab based practical exam	1-8	Written

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Written exam	Written exam (1 hour exam)	1,5,8	August re-assessment period
Practical exam	Practical exam (2 hours lab based practical exam)	1-8	August re-assessment period

Indicative learning resources - Basic reading

The following books are a useful resource for this course:

Evans, J.R., 2017. Business analytics, Global edition England: Pearson
Albright, S.C. and Winston, W.L., 2014. Business analytics: Data analysis & decision making. Cengage Learning

Indicative learning resources - Web based and electronic resources

ELE – College to provide hyperlink to appropriate pages

Indicative learning resources - Other resources

A more comprehensive bibliography will be available to students taking this course

Key words search

Business Analytics, Data Management, Decision Making

Credit value	15
Module ECTS	7.5
Module pre-requisites	None
Module co-requisites	None
NQF level (module)	5
Available as distance learning?	No
Origin date	11/05/2021
Last revision date	05/04/2023