Undergraduate Course: Business Analytics and Information Systems (BUST08032)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course demonstrates how information systems and decision support tools can be effectively integrated to analyse and solve business problems. |
| Course description |
This course discusses how business analytics and information system tools can be used in synergy to address a variety of business problems.
As for the information system part, the emphasis is placed on
1. the illustration of how data can be modelled, stored and retrieved,
2. the application of data management tools to tackle business problems.
The focus of business analytics is on:
1. the introduction of a range of prescriptive analytics tools which has been shown to aid decision-making in practice,
2. the utilisation of software with appropriate data to formulate and execute various models,
3. the explanation of the findings from modelling a managerial situation to the relevant stakeholders.
Outline Content
L 1. Data Management and Database Design
L 2. Entity-relationship
L 3. Structured Query Language
L 4. Introduction to Linear Programming
L 5. Sensitivity Analysis and Advanced Applications in Linear Programming
L 6. Group Project Proposal Presentation
L 7. Introduction to Decision Analysis
L 8. Decision Analysis with Experiment
L 9. Data Visualization
L 10. Guest Speakers and revision
Student Learning Experience
The course is taught by means of lectures, computer labs, tutorials, and group activities. Lectures cover topics in information systems and data management, such as database design and SQL; as well as a number of business analytics techniques, such as linear programming, decision analysis and data visualisation. Computer labs let students acquire the skills that are necessary to apply these techniques in practice by using state of the art software packages. Tutorials provide an understanding of the theory underpinning the aforementioned techniques. Group activities are designed to let students experience challenges and opportunities that stem from the integration of decision support models and information systems.
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Information for Visiting Students
| Pre-requisites | Visiting students must have at least 1 introductory level Business Studies course at grade B or above for entry to this course. We will only consider University/College level courses. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2024/25, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 8,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
163 )
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| Assessment (Further Info) |
Written Exam
40 %,
Coursework
30 %,
Practical Exam
30 %
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| Additional Information (Assessment) |
15% MCQ (Individual) - 1 hour - Assesses course Learning Outcomes 1,2,3,4
15% MCQ (Individual) - 1 hour - Assesses course Learning Outcomes 1,2,3,4
30% Report (Group) - 2,000 words - Assesses all course Learning Outcomes
40% Exam (Individual) - 2 hours - Assesses course Learning Outcomes 2,3,4,5 |
| Feedback |
Formative: Feedback will be provided throughout the course.
Summative: Feedback will be provided on the assessments within agreed deadlines. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Discuss state of the art techniques for data modelling, storage and retrieval in database management systems.
- Transform a verbal business statement into its equivalent mathematical model.
- Demonstrate a sound knowledge of linear programming and sensitivity analysis.
- Demonstrate a good knowledge of decision analysis for business problems with uncertainty.
- Utilise modelling software and solver to formulate business problems and to identify their optimal solutions.
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Reading List
James R. Evans, Business Analytics. Pearson (2nd international edition). 2016 ISBN-13: 978-1292095448
Wayne L. Winston, Operations Research Applications and Algorithms (4th ed.), Brooks/Cole Publishing 1998, ISBN 0534423620
David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, R. Kipp Martin, An Introduction to Management Science: Quantitative Approaches to Decision Making (12th international ed), Cencage 2013, ISBN 978-1-133-58446-9. (Note that other editions of this text have similar content.)
Thomas Connolly, Carolyn Begg, Database Systems: A Practical Approach to Design, Implementation and Management, Global Edition, 6th Edition, Pearson, 2015.
Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research (7th ed.), McGraw-Hill, 2009, ISBN 0071324836
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Additional Information
| Graduate Attributes and Skills |
Communication, ICT, and Numeracy Skills
After completing this course, students should be able to:
Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.
Knowledge and Understanding
After completing this course, students should be able to:
Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.
Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore and solve them responsibly.
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| Keywords | Business Analytics & Information Systems |
Contacts
| Course organiser | Dr Xin Fei
Tel: (0131 6)50 8074
Email: Xin.Fei@ed.ac.uk |
Course secretary | Miss Jen Wood
Tel: (0131 6)50 8335
Email: J.Wood@ed.ac.uk |
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