Undergraduate Course: Business Analytics and Information Systems (BUST08032)
||College||College of Arts, Humanities and Social Sciences
|Credit level (Normal year taken)||SCQF Level 8 (Year 2 Undergraduate)
||Availability||Available to all students
|Summary||This course demonstrates how information systems and decision support tools can be effectively integrated to analyse and solve business problems. (This course was previously entitled BUST08007 Management Science and Information Systems.)
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.
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.
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?
Course Delivery Information
|Academic year 2022/23, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 20,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 8,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Your work will be assessed in three ways:
1. Online time-limited assessments in weeks 4 and 9 (30% of the Final Mark; each contributes to 15% of the Final Mark).
2. Report of 2000 words in which each group of maximum 6 students to report their findings stemming from the analysis of a management decision problem (30% of the Final Mark); peer assessment scores from other group members carried out via WebPA adjusts by 20% the Essay mark for each individual group member.
3. A degree examination (40% of the Final Mark).
||1. Generic feedback on the COMPUTER LAB ASSESSMENTS, together with individual marks, will be posted on Learn during the week following the assessment.
2. Generic feedback on the GROUP COURSEWORK PROJECT, together with individual marks, will be posted on Learn within 15 working days after the submission deadline; also the individual electronic feedback for your group coursework will be accessible through My Grades on Learn.
3. The compulsory TUTORIALS provide the opportunity for testing your understanding and getting direct feedback. The tutorial exercises are posted in the 'Tutorials' folder on Learn and students are expected to complete the exercises before the tutorial so that any problems can be discussed at the tutorial.
4. The EXAMINATION marks will be posted on Learn together with generic feedback and examination statistics as soon as possible after the Board of Examiners' meeting (normally early-mid June). During the summer months (i.e. mid/end June - end August), you may come into the Business School Undergraduate Office (Room 1.11, Business School, 29 Buccleuch Place) to look at your examination scripts. Continuing students will also be given the opportunity to review their examination scripts early in the new academic year in Semester 1 (i.e. in October).
||Hours & Minutes
|Main Exam Diet S2 (April/May)||2:00|
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,
|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
|Graduate Attributes and Skills
1. Design a database suitable for a given dataset.
2. Build a decision support model for a given management decision problem.
3. Integrate a database and a decision support model to derive management recommendations for a given management decision problem.
4. Identify what combination techniques covered is most suitable to address a management decision problem.
Professional Skills/Subject Specific/Practical Skills
1. Model a given set of data using the relational modelling paradigm.
2. Store and retrieve data from a database management system.
3. Build, solve and analyse linear programming or decision analysis models in Excel.
4. Use a project management decision support tool to schedule project activities.
1. Demonstrate report writing skills.
2. Demonstrate problem analysis and problem solving skills.
|Additional Class Delivery Information
||16 lectures (1 hour each)
4 computer labs (1 hour each) in Weeks 2,3,5,9
5 tutorials (1 hour each) in Weeks 4,5,7,8,9
Oral presentation for proposal (3 hours) in Week 6
Guest lecture and Q&A session in Week 10 (2 hour)
|Keywords||Business Analytics & Information Systems
|Course organiser||Dr Xin Fei
Tel: (0131 6)50 8074
|Course secretary||Ms Heather Ferguson
Tel: (0131 6)50 8074