Introduction to Business Analytics
Essex Business School
Undergraduate: Level 5
Sunday 15 January 2023
Friday 24 March 2023
17 August 2022
Requisites for this module
BSC N111 Business Administration and Supply Chain Management,
BSC N112 Business Administration and Supply Chain Management (Including Placement Year),
BSC N113 Business Administration and Supply Chain Management (Including Year Abroad),
BSC N114 Business Administration and Supply Chain Management (including Foundation Year),
BSC N114CO Business Administration and Supply Chain Management (including Foundation Year)
This module will offer an opportunity to develop the knowledge and skills in the domain of business analytics and data science.
It will focus on introducing different tools and approaches to support data analysis and decision making in business environment. The module is designed to enhance students' ability of data analysis to uncover embedded information useful for decision making.
The aim of this module is to:
1. Provide a comprehensive understanding of key tools and methods of business analytics;
2. Develop practical skills and knowledge among students for data analytics and decision making;
3. Build confidence in students to apply data analytics tools and methods to support business decisions.
On successful completion, students will be able:
A. To clearly understand the key concepts and approaches of business analytics and data science.
B. To clearly understand the role of data analytics in effective decision making in practice.
C. To evaluate the potential of data analytics in supporting complex decision making in real-world business environment.
D. To analyse the challenges in implementing business analytics tools and methods in practice.
Introduction to Business Analytics:
Introduction to Business Analytics
Key business intelligence tools for data analysis
Decision making under uncertainty
Optimisation and Simulation methods:
Introduction to optimisation methods
Simulation modelling with risk
Practical simulation modelling models
Advanced Data Analysis:
The following learning and teaching methods will inform the pedagogic structure of the course: lectures, case studies, class exercises, group work, and signposting to other resources and support.
Students will be encouraged and required to refer to a wide range of resources covering textbooks and academic peer reviewed journal articles, to build an understanding of theoretical concepts and refer to online platforms to follow current trends and practices concerning business analytics and decision making tools.
The lectures will be developed around key concepts as mentioned in the indicative module content and will use a range of examples and cases from practice to demonstrate the application of theoretical concepts. The lectures will follow a weekly format of 2 hours (1 hour lecture and 1 hour seminar) per week for 10 weeks.
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's reading list
Assessment items, weightings and deadlines
|Coursework / exam
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Module supervisor and teaching staff
Dr Peng Xu, email: email@example.com.
Mr Peng Xu
No external examiner information available for this module.
Available via Moodle
Of 4 hours, 4 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can
be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements,
industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist
of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules.
The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.