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.)
The goal of this course is to demonstrate how information systems and decision support tools can be used in synergy to address business problems. More specifically, our aim is to:
1. Illustrate how data can be modelled, stored and retrieved in order to effectively support decision making.
2. Introduce a range of quantitative approaches to decision making.
3. Apply state-of-the-art data management and decision support tools to tackle business problems.
1. Data Management and Database Design
2. Linear Programming
3. Project Management
4. Decision Analysis
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 management science techniques, such as linear programming and decision analysis. 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 2020/21, 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. Direct assessment of the work you complete within computer sessions (30% of the Final Mark; each of the 3 computer labs contributing to 10% of the Final Mark).
2. Essay of 1500-2000 words in which each group of 4 or 5 students 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.
- Discuss the key elements of a linear programming model and its underlying assumptions; illustrate possible solution methods for solving linear programs.
- Discuss selected approaches to decision making under uncertainty and illustrate possible solution methods.
- Discuss selected techniques in project management.
- Discuss the key steps that should be executed to tackle a management decision problem.
|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
||20 lectures (1 hour each)
3 assessed computer labs (2 hours each)
5 tutorials (1 hour each) in Weeks 3,5 6,7,10
3 Q&A sessions (30 minutes each) in Weeks 4, 8, 9
|Keywords||Business Analytics & Information Systems
|Course organiser||Dr Yi Cao
Tel: (0131 6)51 5338
|Course secretary||Mr Mark Woodfine-Jones
Tel: (0131 6)50 3825