"Business Analytics in Supply Chains 1" and "Business Analytics in Supply Chains 2" form a unit that prepares students for the complex tasks of building and using systems for business analysis and simulation. In "Business Analytics in Supply Chains 1" students learn how to design and implement a data warehouse as well as decision support and reporting functions on top of the warehouse. This course lays the foundations for the strategic enterprise management and business simulation in "Business Analytics in Supply Chains 2". The course starts with the methodological foundations that are necessary to transform a user requirement for a decision support system into a data warehouse design specification:

• Dimensional Fact Modeling: extraction of a basic warehouse model from information on operational IS,
• Aggregation Path Array: planning the aggregation hierarchies to support specified reporting requirements,
• Logical Model specification of the warehouse.

Each method is immediately applied in a group assignment for a given technical specification and business problem, resp. students then learn to implement the specification incorporated in the above models in a data warehouse product, SAP BW. Each student works in a separate virtual data warehouse implementing the system from scratch. The implementation steps are:

• Defining the multi-dimensional data structures, the time series, and the aggregation hierarchies for high-level aggregates, which are needed for the analytical applications of the data warehouse,
• Defining sources for data imports, data validation and reconciliation schemas,
• Physically loading the warehouse using pre-arranged data thereby filling the above data definitions,
• Defining procedures for periodical data update and the refresh of aggregate data in the warehouse.

Maximum absence time allowed in class: 2 hours. The lecturer has to be informed in advance.

Students are obliged to perform the steps in the case study implementation they missed independently.

Assessment will be based on:-

• 1 hr. written exam in data modelling for data warehouses
• Implementation of the warehouse case study in BW.

Both criteria account for 50% of the overall assessment each

Grading scale:

(1) Excellent: 90% - 100%

(2) Good: 80% - <90%

(3) Satisfactory: 70% - <80%

(4) Sufficient: 60% - <70%

(5) Fail: <60%

Prerequisite for passing the course: minimum performance of 40% in the final examination.

Topics: Entity Relationship Modeling; Event-driven Process Chains

one example of each web trainer:

https://www.wu.ac.at/erp/webtrainer/erm-webtrainer/

https://www.wu.ac.at/erp/webtrainer/epc-webtrainer/

(NOT necessary for regular SCM students!)