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This repo contains a dataset, exercises, and sample code for an end-to-end SAP BTP data-to-value bootcamp covering SAP HANA Cloud, SAP Data Warehouse Cloud, SAP Data Intelligence Cloud, and SAP Analytics Cloud.
This repository aims to onboard new users into Modeling in SAP Data Warehouse Cloud in the most practical manner. For that you will build a real working data model, which will embrace specific features and functions.
The publication is a collection of sample code to show how data from SAP and non-SAP systems can be made available for training in ANY hyperscaler machine learning service via several layers of abstraction from data connection to training using our FedML Python libraries.
This project creates an SAP HANA Deployment Infrastructure (aka HDI) container on SAP HANA Cloud and persists actual sales data originated from an external system in the same SAP Data Warehouse Cloud’s existing persistence area.
The sample integration flows in this repository demonstrate how to use SAP BTP Integration Suite to pull data from the SAP Ariba Analytical Reporting API, process it into SAP Data Warehouse Cloud, and analyze it using the SAP Analytics Cloud Spend Analysis business content.
This sample tool shows how to programmatically create, update, and delete SAP Data Warehouse Cloud artifacts. The tool, referred to as **provisioner**, is written in Python and demonstrates how to automate various SAP Data Warehouse Cloud provisioning activities.