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Data warehousing and business intelligence

  • Class 30
  • Practice 30
  • Independent work 90
Total 150

Course title

Data warehousing and business intelligence

Lecture type


Course code






Lecturers and associates

Course overview

The objectives of this module are to enable students to:
• Analyze data warehouse characteristics and plan warehouse data (Dimensions, Facts, Hierarchies, Rollups)
• Illustrate trends towards data warehousing and dana mining
• Critically use all the data transformation processes
• Estimate hardware infrastructure requirements
• Compare data warehouse modelling alternatives and
• Design and implement a data warehouse

In this module students will learn to understand and follow methodologies and technologies used for implementation of analytical information systems based on data warehouses.

It is important for students to take this module so that they learn and understand the methodological knowledge necessary for implementing data warehouses, reporting systems and multi-dimensional analysis and implementing systems for planning and budgeting, predictive analysis and big data analysis.

Through practical engagement students will learn how to use Microsoft tools for developing analytical systems needed for other modules in this study programme.


Essential reading:
1. Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., Becker, B. (2008) The Data Warehouse Lifecycle Toolkit, 2nd Edition, Hoboken: Wiley
2. Laberge, R., (2011) The Data Warehouse Mentor: Practical Data Warehouse and Business Intelligence Insights, New York: McGraw-Hill Education

Recommended reading:
1. Connolly, T., Begg, C., Strachan., A. (2014) Database Systems: A Practical Approach to Design, Implementation and Management, London: Pearson

Minimal learning outcomes

  • Explain basic concepts of DW
  • Explain most usual data and data quality issues.
  • Describe process of data integration from different sources and suggest most appropriate a data integration platform.
  • Explain and critically discuss user requirements for the analytical system.
  • Explain basic OLAP structures, define basic reports and dashboards.
  • Explain key roles and their responsibilities in the implementation of the analytical system.

Preferred learning outcomes

  • Design a data warehouse
  • Analyze operational data and data quality issues.
  • Integrate data from different sources using a data integration platform.
  • Specify user requirements for the analytical system.
  • Design OLAP structures, create reports and dashboards.
  • Participate in the implementation of the analytical system as a team member.
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