Data Warehousing and Data Mining

Programme Overview

You will learn the fundamentals of data warehousing and data mining. You will gain a deeper understanding of how data mining is used through hands-on experience in various areas such as big data analysis, prediction, classification, identification, clustering, and association. In addition, you will learn how data mining and databases work hand-in-hand from a user perspective in various data modelling, statistical analysis, designing schemas, querying databases, and manipulating databases. By the end of the course, you will understand key strategies on how to apply data mining technology to real-world applications, evaluate trends, and optimal design solutions.

Learning Outcomes

1. Develop knowledge of database technologies and purpose of data mining types (such as predictive, classification, identification, and optimisation) that are used to discover specifics details such as relationships and patterns in data
2. Review various techniques used to discover information from data sets that can be used in various application areas such as in database marketing for retail, credit management, fraud detection, manufacturing or product design, and medicine to understand how solutions are implemented and overall usability. 
3. Utilise data mining tools and programming techniques such as RapidMiner for Python, Oracle Data mining or open-source tools to develop knowledge on how they can be used in specific scenarios and situations to draw hypotheses from data sets. 
4. Design solutions to apply data mining to obtain an expected outcome, analyse trends, or identify results based on data or information stored in a data warehouse for real-world business process and business decisions.
5. Describe scenarios to determine how to optimise data to train models when results are not producing the expected results and impact to performance.