Businesses generate huge amount of data that relates to different aspects of their operations, investing and financing decisions. Business entities live in the environment where further information comes from multiple sources. Understanding ways to accumulate such data, manage it strategically and use it to develop business insights is critically important. 
This unit provides students with understanding of various data mining tools, techniques and frameworks for analysing and interpreting business data. The focus of this unit is on business needs and applications of data mining tools, including applications of data mining in the cloud. In particular, the unit reviews data pre-processing methods of dealing with noisy data and evaluation and analysis of data mining models in the context of big data. The unit covers such important aspects of data warehousing, as architecture, design, implementation, and optimisation, including working with cloud technologies and big data. Students are provided with hands-on experience in data warehousing using relational and non-relational management systems, and multi-dimensional modelling for structuring business intelligence data.

Unit details

Study level:
Postgraduate
Credit points:
12
Unit code:
BCO7004

Learning Outcomes

On successful completion of this unit, students will be able to:
  1. Deconstruct complex business problems into data mining and warehousing solutions, data requirements and data models using relational databases;  
  2. Design and 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.  

Assessment

Assessment type Description Grade
Exercise Collaborative learning Exercises - Group 25%
Project Written project on data warehousing 40%
Exercise Developing and evaluating a reporting solution - Group 35%

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