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MODULE DESCRIPTOR
Module Title
Business Intelligence Tools and Applications
Reference CMM725 Version 3
Created February 2024 SCQF Level SCQF 11
Approved April 2017 SCQF Points 15
Amended April 2024 ECTS Points 7.5

Aims of Module
To gain an in-depth knowledge of business intelligence concepts, methods and tools for solving business problems.

Learning Outcomes for Module
On completion of this module, students are expected to be able to:
1 Make informed judgements on state-of-the-art business intelligent tools for industrial applications.
2 Make informed judgements on data visualization techniques used in the industry that are specifically used to derive business intelligence from data.
3 Design a multidimensional analysis of business data and interpret results from complex trend and other analysis using state-of-the-art modelling techniques.
4 Produce a solution to a business problem using data visualization techniques using a selected state-of-the-art tool and communicate these insights and recommendations.

Indicative Module Content
Decision support systems (DSS): types of decisions managers face, DSS types and classification and evolution of DSS over time. Data Visualisation and Dashboard Techniques: basic and composite charts, list attributes of metrics usually included in dashboards, use a dashboard design tool for a real-word business problem. Business Performance Management: four phases of BPM cycle, key performance indicators (KPIs), differences between dashboards and scorecards. Business Intelligence tools: Cubes, Reporting, ad-hoc query tools, visualisation tools such as Tableau and Qlikview.

Module Delivery
This is a lecture based course enhanced through interactive tutorials and directed reading, supplemented with laboratory sessions where state-of-the-art visual modelling tools will be used to teach key concepts and tools of business intelligence.

Indicative Student Workload Full Time Part Time
Contact Hours N/A 48
Non-Contact Hours N/A 102
Placement/Work-Based Learning Experience [Notional] Hours N/A N/A
TOTAL N/A 150
Actual Placement hours for professional, statutory or regulatory body    

ASSESSMENT PLAN
If a major/minor model is used and box is ticked, % weightings below are indicative only.
Component 1
Type: Coursework Weighting: 100% Outcomes Assessed: 1, 2, 3, 4
Description: Coursework submission worth 100% of total module assessment.

MODULE PERFORMANCE DESCRIPTOR
Explanatory Text
The calculation of the overall grade for this module is based on 100% weighting of C1. An overall minimum grade of D is required to pass the module.
Module Grade Minimum Requirements to achieve Module Grade:
A The student needs to achieve an A in Component 1.
B The student needs to achieve a B in Component 1.
C The student needs to achieve a C in Component 1.
D The student needs to achieve a D in Component 1.
E The student needs to achieve an E in Component 1.
F The student needs to achieve an F in Component 1.
NS Non-submission of work by published deadline or non-attendance for examination

Module Requirements
Prerequisites for Module None.
Corequisites for module None.
Precluded Modules None.

INDICATIVE BIBLIOGRAPHY
1 MIKE, B., 2003. Business Intelligence for the Enterprise. Prentice Hall PTR.
2 SHERMAN R., 2014. Business Intelligence Guidebook: From Data Integration to Analytics. Morgan Kaufmann.
3 BOYER J. and FRANK B., 2010. Business Intelligence Strategy: A Practical Guide for Achieving BI Excellence. Mc Press.
4 MOSS L.T. and ATRE S., 2003. Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Addison-Wesley Professional.
5 SHARDA R., DELEN D. and TURBAN E., 2013. Business Intelligence: A Managerial Perspective on Analytics. 3rd ed. Pearson.

Robert Gordon University, Garthdee House, Aberdeen, AB10 7QB, Scotland, UK: a Scottish charity, registration No. SC013781