Course information

Learning Outcomes

Data Warehouses (DWH) store big amounts of data in databases designed with a focus in data analysis. Business Intelligence is the process of extracting information from DWH with the purpose of enabling decision support. In this course students will learn about different DWH architectures and processes. They will be able to differentiate between "normal" databases and DWH. Students will learn basics of dimensional data modelling and gain practical MDX, OALP, and SQL coding experience in addition to understanding of ETL processes and selected methods for data analysis. Furthermore, students will have the opportunity to work with datasets in a data warehouse environment and apply learned skills in practice using tools such as IBM DB2, MYSQL, Pentaho Data Integration tool, and KNIME

Content

The comprehensive thematic of this course is organized in two blocks. In the first block, the development and management methods for DWH in relational databases are presented (e.g., architectures, multidimensional data model, ETL-process, OLAP operations, multidimensional queries, Bitmap-index, view materialization). In the second block, topics in knowledge discovery and data mining in DWH are presented (e.g., discovering frequent patterns, associations rules, clustering and classification, prediction). In addition, current research and recent trends in DWH are also addressed (with guest lecturers)