Module Database Search



MODULE DESCRIPTOR
Module Title
Data Warehousing
Reference CMM701 Version 2
Created October 2017 SCQF Level SCQF 11
Approved May 2016 SCQF Points 15
Amended November 2017 ECTS Points 7.5

Aims of Module
To provide key concepts and principles of data warehousing techniques and to develop specialised knowledge in areas that demonstrate the interaction and synergy between research and practices of distributed large-scale data stores.

Learning Outcomes for Module
On completion of this module, students are expected to be able to:
1 Critically appraise data warehousing design principles, practices and standards.
2 Compare and contrast methodologies that are at the forefront in data warehousing design and development.
3 Design a multidimensional analysis of business data and interpret results from complex trend analysis using state-of-the-art modeling algorithms.
4 Create a data warehousing solution by adopting and extending methods that are informed by current research and industry practices.

Indicative Module Content
Data Capture, data cleaning, data conformation, data integration, data federation and data virtualisation. Concepts and benefits associated with data warehousing. Conventional, spatial and temporal data warehouses. Architecture of a data warehouse. Data warehouse design. Tools for Data warehousing. State of the art in data warehousing, including data warehousing in the cloud. Data warehousing with big data Case studies.

Module Delivery
Key concepts are introduced and illustrated through lectures and directed reading. The understanding of students is tested and further enhanced through interactive tutorials. In the laboratories the students will progress through a sequence of exercises to further their understanding and gain practical experience of data warehousing.

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: 50% Outcomes Assessed: 1, 2
Description: Written report.
Component 2
Type: Coursework Weighting: 50% Outcomes Assessed: 3, 4
Description: Coursework involving the development of a data warehousing application.

MODULE PERFORMANCE DESCRIPTOR
Explanatory Text
The calculation of the overall grade for this module is based on 50% weighting of C1 and 50% weighting of C2. An overall minimum grade D is required to pass the module.
Coursework:
Coursework: A B C D E F NS
A A A B B C E
B A B B C C E
C B B C C D E
D B C C D D E
E C C D D E E
F E E E E E F
NS Non-submission of work by published deadline or non-attendance for examination

Module Requirements
Prerequisites for Module None except for course entry requirements.
Corequisites for module None.
Precluded Modules None.

INDICATIVE BIBLIOGRAPHY
1 CONNOLLY, T. and BEGG, C., 2015. Database Systems: A Practical Approach to Design, Implementation and Management. Pearsons.
2 KIMBALL, R., ROSS, M., 2013. The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling (3rd Edition). John Wiley & Sons, Inc.
3 MOHANTI, S., 2013. Big Data imperatives- enterprise big data warehouse, BI implementations and analytics. Apress.
4 SILVERS, F., 2008. Building and maintaining a data warehouse. CRC Press.

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