Module Descriptors
DATA WAREHOUSING
COMP40013
Key Facts
Digital, Technology, Innovation and Business
Level 4
20 credits
Contact
Leader: Euan Wilson
Email: E.D.Wilson@staffs.ac.uk
Hours of Study
Scheduled Learning and Teaching Activities: 65
Independent Study Hours: 135
Total Learning Hours: 200
Assessment
  • Written Assessment - Case Study and Datawarehouse - 1500 words weighted at 50%
  • Presentation - 10 minutes weighted at 50%
Module Details
Module Learning Outcomes
1) Critically discuss and evaluate domain-specific techniques for creation of Data Warehouses with respect to different disciplines.
Knowledge and Understanding

2) Research, analyse and critically evaluate best practices in Data Warehousing.
Analysis, Problem Solving, Application, Reflection

3) Test and develop systematic analytical approaches to problem solving that emphasize best solutions to data warehousing scenarios.
Analysis, Problem Solving, Communication
Module Additional Assessment Details
Assignment 1 - Case study to model a business problem and to build a data warehouse. Learning Outcome 1 to 3

Assignment 2 - A supporting presentation to accompany Assignment 1. Learning Outcome 1-3.
Module Indicative Content
The content of this module includes:
• Concepts of Data Warehousing
• Data Warehousing design approaches
• Architectures, schemas, tuning, loading, etc.
• Dimensional modelling
• Performance issues
• Kimball and Inmon
• Data lakes
• Issues of data cleansing
• Data governance
• Data integration
• Data transformation
• Working with structured and unstructured data
• Using Data Warehousing techniques with a relational database
Module Learning Strategies
2x 1 hour lecture a week, and 1 x 3 hour practical session a week. Theoretical elements will be integrated into the practical sessions in order that you learn the theory behind Data Warehousing and directly apply it in the practical sessions.
Module Web Descriptor
This module looks at creating and utilising Data Warehousing techniques, and examines two of the most popular styles (Kimball and Inmon). In studying it you will explore Data Warehousing from many angles and topics which include design approaches, architecture, modelling, working with data, cleansing, and data governance. The knowledge learned in this module will readily transfer to your other study modules.
Module Texts
Marr, B. (2016) Big data in practice: how 45 successful companies used big data analytics to deliver extraordinary results Wiley ISBN: 1119231388; 9781119231387
Data Protection Act 2018 and GDPR 2018
Ladley J. (2012) Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program Morgan Kaufmann ISBN-13: 978-0124158290 0124158293
Module Resources
SQLserver
Oracle