Business Data Mining and Warehousing

This unit provides students with the knowledge and skills to use data mining tools, techniques and frameworks for analysing and interpreting business data. Students use data mining tools, including applications of data mining in the cloud, to develop business insights to support decision-making. The unit covers important aspects of data warehousing including architecture, design, implementation, optimisation, working with cloud technologies and big data. Students engage in hands-on experience undertaking data warehousing using relational and non-relational management systems for structuring business intelligence data. The data mining applications include working with Application Programming Interface (APIs), data scraping, data aggregation, protocols for storing and transporting data. The unit pays particular attention to data efficacy, open data and wild caught data.

Learning Outcomes

On successful completion of this unit, students will be able to:

1. Troubleshoot complex business problems through the application of data mining and warehousing solutions using relational databases;
2. Critically reflect upon data warehousing architecture and multidimensional data models using internal and external business data;
3. Implement online analytical processing (OLAP) in SQL and devise business intelligence reports using data warehouses and OLAP; and,
4. Critically evaluate big data processing frameworks and technologies, contextualise the use of NoSQL technologies, implement and critically evaluate streaming methods in big data processing.