Class Datawarehouse Techniques

The discipline Data Warehouse Techniques has as its fundamental objective present to the student the importance of a Data Warehouse architecture and its impact on data solutions in the business world. This curricular unit will introduce students to the motivations behind the genesis of the Data Warehouse, its main features in data storage and modeling, as well as the latest solutions such as Data Lake and Data Lakehouse applied by large technology companies. In the practical component, the student will have the opportunity to apply the concepts taught in the theoretical component, in a technology that is highly valued in the current job market.

Not applicable

Theoretical classes Trends in Data, Analytics and Business Intelligence Data Warehouse Architecture Multidimensional Modeling Data Warehouse Techniques OLAP systems Practical classes Introduction and Setup of Power BI Data Connection and Transformation Relational Model Creation DAX - Calculated Fields Data Visualization Other PowerBI Components

The course is split into theoretical and practical classes. Students are evaluated on: Project (50%) to build a relational model from a set of data and a report presentation; Final exam (50%) with multiple choice questions and development questions. To be approved, the project grade must be higher than 9.5 and the final test grade must be higher than 9.5.

Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling (Third Edition). Indianapolis, IN: John Wiley & Sons, Inc. Santos, M., & Ramos, I. (2017). Business Intelligence Da Informação ao Conhecimento (3ª Edição Atualizada). FCA Editora de Informática, Lda.