Data Science and Artificial Intelligence

Analytical Information Systems

Integrated course, 5.00 ECTS

 

Course content

Part 1: ETL or ETL processes
- Basics of ETL resp. ETL processes
- Planning and creation of ETL workflows
Part 2: Multidimensional resp. OLAP databases
- Basics of multidimensional resp. OLAP databases
- Planning and creation of multidimensional resp. OLAP databases
- Access to multidimensional resp. OLAP databases
- Introduction to the query language MDX
- Data mining using multidimensional resp. OLAP databases
Part 3: Business Intelligence resp. Business Analytics
- Introduction to business intelligence and business analytics
- Overview of important solutions in the area of business intelligence and business analytics
- Overview of important solutions in the area of self-service BI

Learning outcomes

Students are able to plan and create ETL processes. They are also able to plan and create multidimensional resp. OLAP databases and to access the contained data efficiently. Finally, students will also get an overview of important solutions in the areas of business intelligence, business analytics and self-service BI.

Recommended or required reading and other learning resources / tools

Recommended literature or books:
- Azevedo, P., Brosius, G. et al (2009). Business intelligence and reporting with Microsoft SQL Server 2008. Microsoft, 1st edition.
- Inmon, W.H. (2005). Building the data warehouse. Wiley, 4th edition.
- Kimball, R. (2007). The Data Warehouse Lifecycle Toolkit, 2nd Edition. Wiley, 2nd edition.
- Kimball, R. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition. Wiley, 3rd edition.
- Kimball, R., Caserta, J. (2004). The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data. Wiley, 1st edition.
- Mertins, D., Neumann, J. et al (2016). SQL Server 2016: Das Programmierhandbuch. Inkl. ADO.NET Entity Framework und Migration von SQL Server 2014. Rheinwerk Computing, 7. Auflage.
Recommended journals or selected articles:
Relevant journals and articles will be announced in the course.

Typical software for this module:
Microsoft SQL Server, Microsoft SQL Management Studio, Microsoft Power BI, Microsoft Excel etc.

Mode of delivery

2,5 ECTS Lecture, 2,5 ECTS Exercise

Prerequisites and co-requisites

Module 4

Assessment methods and criteria

Lecture: final exam, Exercise: examination character