Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Saturday | 12/17/22 | 09:00 AM - 05:00 PM | LC.-1.038 |
Friday | 12/23/22 | 08:30 AM - 12:30 PM | LC.2.064 PC Raum |
Friday | 01/20/23 | 03:00 PM - 06:00 PM | TC.3.02 |
Saturday | 01/21/23 | 09:00 AM - 05:00 PM | LC.-1.038 |
This subject is based upon "Business Analytics in Supply Chains 1" and provides in-depth case studies using SAP Hana that come very close to real-world data warehouse build and maintenance scenarios.
Students understand concepts and ways to implement organisation-wide data reconciliation and data management in an in-memory data warehouse setting. They understand the link, but also the differences between operational data store, such as for ERP systems and analytics data bases. They also understand how analog data fit into an organisation-wide analytics strategy.
According to the examination regulation full attendance is intended for a PI.
Based upon the data warehouse skills of "Business Analytics in Supply Chains 1", a BW data model for process mining will be built. The data represents a typical sales process (quote, order, delivery) and enable to calclulate process metrics but also check for process anomales. Questions, such as how long does it take on average to deliver an order or how often is the order quantity changed are answered and analysed along different dimensions, such as customer or material. The course also takes real-world issues into consideration, such as deficient data quality and how to deal with it when building the data warehouse.
Assessment will be based on:
- Implementation of the case study in SAP HANA implemented in class (33,3%)
- Implementation of other case studies in homework (66,7%)
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.
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