Base Knowledge
Information Systems
Relational Databases
Programming Languages (c, c++, php, asp, or java)
Teaching Methodologies
The theoretical classes will be aimed at presenting content and complemented with practical problems to promote and stimulate collective discussion.
In the practical classes, some exercises will be conducted focusing on the implementation of small projects using development tools such as SQL Server, Visual Studio, Excel, and PowerBI.
Learning Results
Understanding the techniques and implementation models of warehousing, including the design and implementation of applications for data extraction, transformation, and integration.
Development and implementation of applications for multidimensional database systems.
Having knowledge in specific aspects of Information Systems (IS).
Being proficient in using various technologies employed in IS within the field of Business Intelligence.
Program
SCM and CRM. Development methodologies for Information Systems. Data Warehousing Systems: Introduction to data warehousing; data warehousing as the informational infrastructure of an organization; environment and functional structure of a data warehouse; life cycle and incremental development of a data warehouse. Project, implementation, and administration of a data warehouse, including aspects of data extraction, transportation, transformation, and integration systems. Modeling tools. Analytical Processing Systems (OLAP): Fundamentals of analytical data processing; data structures for analytical data processing; optimization and dynamic restructuring of cubes; materialization of views: centralized and distributed perspectives. Administration of multidimensional database management systems. Development of projects for multidimensional database systems; definition of data access criteria. Use of analytical processing systems. Development of information systems projects using Visual Studio + SQL Server + Excel + PowerBI Desktop.
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
Ramos, I., & Santos, M. Y. (2017). Business Intelligence: Da Informação ao Conhecimento (3ª ed.). FCA.
Kimball, R., & Ross, M. (2002). The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (2nd ed.). Wiley Computer Publishing.
Inmon, W. H. (2005). Building the Data Warehouse (4th ed.).
Magalhães, A. (2017). Business Intelligence no SQL Server. FC.
Laudon, K., Laudon, J., (2019), Management Information Systems (12ª ed.), Pearson. Cota 1A-13-64
Han, J., Kamber, M., (2006), Data Mining: Concepts and Techniques, Morgan Kaufman. Cota 1A-19-11, 1A-19-20
Kimball, R., & Caserta, J. (2004). The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming and Delivering Data. Wiley Technology Publishing.
Allington, M. , (2018), Supercharge PowerBI, (1st ed), Kindle