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MODULE DESCRIPTOR
Module Title
Business Intelligence
Reference CM3709 Version 2
Created January 2023 SCQF Level SCQF 9
Approved June 2019 SCQF Points 30
Amended June 2023 ECTS Points 15

Aims of Module
To provide students with an in-depth knowledge of business intelligence and data warehousing 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 Critically evaluate state-of-the-art business intelligence tools to support decision-making.
2 Compare and contrast different methods of visualising data appropriate to various stakeholders.
3 Compare and contrast different methods for data integration and master data management.
4 Design, implement and evaluate a data warehousing solution for a business problem, including the application of techniques for the extraction, transformation and loading of data from various sources.

Indicative Module Content
Business Intelligence (BI) systems and types of decisions managers face. Data Visualisation and Dashboard Techniques. Mapping data to visual representations; awareness of accessibility issues. Data integration, data federation and data virtualisation. Data lakes. ETL (Extraction, Transformation and Loading). Master Data Management. Multi-Dimensional Data Analysis. Concepts and benefits associated with data warehousing. Architecture of a data warehouse. Tools for Data warehousing.

Module Delivery
The module is delivered in Blended Learning mode using structured online learning materials/activities and directed study, facilitated by regular online tutor support. Workplace Mentor support and work-based learning activities will allow students to contextualise this learning to their own workplace. Face-to-face engagement occurs through annual induction sessions, employer work-site visits, and modular on-campus workshops.

Indicative Student Workload Full Time Part Time
Contact Hours 30 N/A
Non-Contact Hours 30 N/A
Placement/Work-Based Learning Experience [Notional] Hours 240 N/A
TOTAL 300 N/A
Actual Placement hours for professional, statutory or regulatory body 240  

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: This coursework will consist of a practical development and a written evaluation of a business intelligence solution.

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 D is required to pass the module.
Module Grade Minimum Requirements to achieve Module Grade:
A The student must achieve an A in C1.
B The student must achieve a B in C1.
C The student must achieve a C in C1.
D The student must achieve a D in C1.
E The student must achieve an E in C1.
F The student must achieve an F in C1.
NS Non-submission of work by published deadline or non-attendance for examination

Module Requirements
Prerequisites for Module None, in addition to course entry requirements.
Corequisites for module None.
Precluded Modules None.

INDICATIVE BIBLIOGRAPHY
1 SHERMAN R., 2014. Business Intelligence Guidebook: From Data Integration to Analytics. Morgan Kaufmann.
2 SHARDA R., DELEN D. and TURBAN E., 2014. Business Intelligence: A Managerial Perspective on Analytics. 3rd ed. Pearson.
3 KIRK, A., 2016. Data Visualisation, A Handbook for Data Driven Design. Sage Publishing.
4 VAISMAN, A., 2014. Data warehouse systems: design and implementation. Springer.
5 DAMA International., 2017. DAMA-DMBOK: Data Management Body of Knowledge. 2nd Ed. Technics Publications.

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