README.md

Data Modeling&Processing

In this section, we'll perform the following exercises

End-to-end Modeling with SAP Data Warehouse Cloud for Book Sales Analysis
End-to-end Machine Learning with SAP Data Intelligence Cloud for
- Book Recommendation
- Book Genre Clustering

DV200_Exercise01: Create a Book Author view with Graphical View of Data Builder
Demo Video
DV200_Exercise02: Create a Data Flow to union the current sales orders in SAP S/4HANA Cloud and archived historic sales order in AWS S3, and persist the result as a local table.
Demo Video
DV200_Exercise03: Create a Dimension based on Book Author view
Demo Video
DV200_Exercise04: Create a Analytical Dataset about All Book Sales Orders based on result of DV200_Exercise02 with association to Book Author Dimension and Day Dimension.
Demo Video
DV200_Exercise05: Create a Comsumption Model based on the analytica dataset created in DV200_Exercise04, and create a perspective for the consumption model about All Book Sales Order with all fields.
Demo Video
DV200_Exercise06_Bonus_Exercise: This is a bonus exercise about modeling, which let you explore different options of modeling for the same use case. In this exercise, you will create another graphical view with data builder based on the book author view created in DV200_Exercise01, the time dimension-day view, and all_book_sales_order local table in DV200_Exercise02, which can produce the same output as DV200_Exercise05 for consumption.