Foundation degrees

Course Information

Data Warehousing

Module summary

Module code: COMP1434
Level: 7
Credits: 15
School: Liberal Arts and Sciences
Department: Computing and Information Sys.
Module Coordinator(s): Mohammad Majid Al-Rifaie



The list below provides the aims for this module:

• To encourage a critical assessment of the use of business intelligence tools in finding timely answers to critical business questions.
• To advance the student's knowledge of the business potential of organising and utilising data to support cross-functional systems.
• To develop the student's practical skills in defining an architecture of a Data Warehouse and in capturing, cleaning, transporting and applying data in a Data Warehouse.
• To develop the student's skills in querying, reporting and using tools to summarize and discover new patterns in the data.

Learning outcomes

On successful completion of this course a student will be able to:

1 Have a sound understanding of how a data warehouse can be used to find answers to critical business questions, while choosing a structure for data that allows it to be used across many applications.
2 Design a data warehouse technology architecture and system to represent a business or organisation. This system will be able to generate the reports needed by management by means of OLAP tools required to analyse data from the data warehouse.
3 Design and implement procedures to automate data transfer into a data warehouse from various sources while also managing the metadata, query performance.
4 Being able to critically analysis the existing systems and infrastructures, making sure they are suitable for the target enterprise.

Indicative content

• Data Quality
• Strategic delivery of information
• Decision Support Systems
• Analytical Processing requirements
• Managing Metadata
• Data Warehouse strategy
• Data Warehouse architecture
• Data Warehouse design - star schemas, fact table, cube
• Capturing, cleaning and transporting data from legacy systems and operational systems
• Querying Reporting and using data analysis tools
• Issues of performance for Very Large DBs
• Tuning the Data Warehouse
• OLAP and Multidimensional databases
• Distributed Databases
• Data replication
• Data Presentation
• Data Mining Warehouses.
• Critical analysis of the time dimension and its impact on the analysis
• Ability to recognise compromises in design with regard to resources

Teaching and learning activity

Concepts will be introduced during lecture or classroom sessions featuring lecturer
presentations and problem-solving sessions using individual and group work to enable students to develop design skills, discuss concepts and plan and design a data warehouse. Supervised laboratory sessions will be used to provide students with the technical skills required to build Data Warehouse systems. Specific laboratory exercises will be provided. Time will be divided equally between lecture presentations, problem and laboratory sessions.

Learning Time (1 credit = 10 hours)


Coursework 1, Logbook - 20% weighting, 50% pass mark.
Outline Details - Log book upload of tasks and questions provided in tutorial and lab sessions.

Coursework 2 - 80% weighting, 50% pass mark.
Outline Details - Building a data warehouse.

Students are required to pass all elements of summative assessment in order to pass the course.