Business Analytics for Managers and Entrepreneurs
Essex Business School
Postgraduate: Level 7
Monday 15 January 2024
Friday 22 March 2024
29 June 2023
Requisites for this module
MSC N11112 Business Analytics,
MSC N111JS Business Analytics,
MSC N21612 International Logistics and Supply Chain Management
This module shows how data analytics is a crucial skill to have in today's business world, and will illustrate this with real world examples where businesses have harnessed the power to solve critical problems. It then aims to equip students with a wide variety of data mining, visual and analytical techniques which can be applied to data generated from different markets, businesses, and business functions.
Data analytics represents a massive opportunity for business leaders, managers and entrepreneurs alike in modern globalised economies. In today's Information and Communication Technology (ICT) led business world, the nature of data has moved from static spreadsheets to being highly interactive dynamic representations from multiple sources, which provide rich insights on markets, firms, competitors, consumers and networks.
The aims of this module are:
- To gain an appreciation of how business analytics can equip managers and entrepreneurs with critical tools and technologies, which would enable them to use freely available information for their own benefit.
- To gain an awareness of what tools and technologies exist which can be freely used to harness the power of analytics on data sets of varying sizes and content.
- To gain essential analytical skills of handling, analysing and manipulating data in order to generate insights about businesses, markets, consumers and competitor.
- To learn simple but powerful visualisation techniques which can reduce the complexity in large data sets.
- To use simulations to explore scenarios and optimise decision making in different business functions and markets.
By the end of this module, students will be expected to be able to:
- Have obtained a critical understanding of principal theoretical approaches to analysing large data sets available in the modern business world.
- Have developed key analytical skills of analysing these datasets using modern computational tools and techniques from a practitioners’ point of view.
- Have gained overall perspective on the importance of data analysis and other quantitative techniques in both strategic and tactical decision making faced by managers and entrepreneurs in the modern business world.
- Evaluate typical data related questions faced by managers and entrepreneurs, and be able to devise analytical strategies to tackle these problems.
- Critically differentiate between the questions which can be tackled using quantitative methods and large data sets and which cannot be answered using the same, but which requires a mixed approach.
No additional information available.
This module will be delivered via:
The lectures will be developed around the key theoretical concepts of data analysis, alternative methods and multiple toolkits. They will also address the issue of multiplicity of analytical requirements when it concerns actual practical applications, and hence will provide a rounded view of how to choose between different methodologies, based on the nature of the question posed as well as nature and source of available data.
The seminars will focus on practical aspects of using the material taught in lectures for solving real life problems. They will use freely available datasets in addition to established software toolkits, both advanced and basic, in order to develop the ability to query the datasets using alternative approaches, understanding the results of such queries and evaluating them in the context of the business problem.
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 Debabrata Ghosh, email: email@example.com.
Dr Wen Zhang
Dr Ping Zheng
Canterbury Christ Church University
Prof Wantao Yu
University of Roehampton
Professor of Supply Chain Management
Available via Moodle
Of 22 hours, 22 (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.
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