ECE422 Data Mining

Introduction to data warehouses. Design, implementation and use of data warehouses. Multidimensional data model. Data cube and its processing. On-Line Analytical Processing (OLAP) in data warehouses. Differences between OLTP (On-line Transaction Processing) and OLAP. Data transfer from existing databases – procedures of extraction, transformation and loading (ETL). Processing of queries in data warehouses. Introduction to data mining. Data preprocessing. Data mining primitives, languages, and system architectures. Concept description: characterization and comparison. Mining association rules in large databases. Classification and prediction. Clustering. Mining data of complex type, e.g. text, images, web data.

Through this course, a student is expected to:

• Acquire knowledge on applications, concepts, techniques and stages of Data Mining and Knowledge Discovery
• Acquire knowledge on Data Warehouses and OLAP
• Develop the ability to estimate the complexity of applying Data Mining for solving problems
• Acquire knowledge and develop skills on modeling Data Mining problems and selecting / developing techniques for their solution