APPLIED ANALYTICS IN BUSINESS - 2024/5
Module code: MAN3201
The module provides an insight into how and why Business Analytics is used by real organisations. It uses a mix of theory and real life cases to explore how Business Analytics methods are used to deliver insights and make faster, better decisions.
Students will gain knowledge on how to think about developing an analytics project, and what the possible challenges are in a real-life context, with less depth in the theoretical foundations of the techniques.
Surrey Business School
HILL Andrew (SBS)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 96
Lecture Hours: 22
Laboratory Hours: 11
Guided Learning: 10
Captured Content: 11
Prerequisites / Co-requisites
MAN2188 - Fundamentals of Business Analytics
An example of the weekly lecture content. Computer labs will allow students to put into practice what they learnt in the lecture, using software such as Excel, Tableau Prep (data wrangling) and Tableau Desktop (data visualisation and data dashboards).
Introduction to the course
Problem-solving in real life
Exploratory Data Analysis I - categorical variables
Exploratory Data Analysis II - continuous variables
Real-life Case Study I
Real-life Case Study II
Statistics you need to know
Business Intelligence and putting it all together
|Assessment type||Unit of assessment||Weighting|
|Coursework||Applied Analytics project||30|
|Oral exam or presentation||Applied Analytics project presentation||20|
|Examination||Applied Analytics Examination 120 min||50|
Alternative Assessment for ‘Applied Analytics Group Project’ is an Individual project
The assessment strategy is designed to provide students with the opportunity to demonstrate:
Knowledge of practical business analytics processes
Appreciation of the need to deliver fit-for-purpose solutions that aid decision-making
Ability to apply key techniques that enable robust insights, including not only analytical but process methods.
Thus, the summative assessment for this module consists of:
Applied Analytics Project (50%)
Group coursework project to be submitted at the end of the semester
Applied Analytics Examination (50%)
2-hour closed book examination taken at the end of the semester.
Online assessments tied to lab sessions
Students will be given the opportunity to receive formative assessment and feedback relevant to the assignments. Formative assessment will also be relevant to the closed book exam may be provided on SurreyLearn discussion forums.
Group feedback on lab session results – common errors, examples of good practice.
Individual feedback after online assessment covering key concepts.
- To Introduce students to the practical methods of data analytics in business that turn theory into applied decision support
- To work with real, messy data and solve real, messy problems.
- To effectively use analytics techniques to improve Return on Investment.
|001||Apply analytics in everyday business practice.||KP|
|002||Effectively apply a range of key methods and processes for delivering key for purpose analytics.||KPT|
|003||Critically appraise business questions and identify analytical techniques most suited to deliver insights||CPT|
|004||Manage and analyse real, messy data||KCPT|
|005||Solve novel business problems by using state-of-the-art analytical techniques and tools||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
Encourage a critical understanding of the importance of the practical application of Business Analytics, where proponents will have to deal with messy data sources, unclear business questions and integrate them all to develop useful insights for decision-making. The course aims are to introduce students to the data-driven decision-making process and to teach them valuable practical skills to solve common data problems.
The course will be very practical, encouraging students to get hands-on with real-life business questions and messy data, and teach them how to solve business problems with robust processes and methods that can handle diverse data sources and business leaders who don’t know what they want!
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: MAN3201
Being able to apply analytic tools in business contexts in key for students to be employable and make sustainable and resourceful decisions based on data. This module deepens their practical understanding and proficiency with digital capabilities required in any corporate environment.
Programmes this module appears in
|Business Management BSc (Hons)||1||Optional||A weighted aggregate of 40% overall and a pass on the pass/fail unit of assessment is required to pass the module|
|Accounting and Finance BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Business Management (Marketing) BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Business Management with Human Resource Management BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Business Management with Business Analytics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Business Management with Entrepreneurship and Innovation BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Accounting and Finance (Dual degree with SII-DUFE ) BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.