SAP-samples/asug-handson

آخر نشاط مصدر مسجل: ٢٦ أكتوبر ٢٠٢٦ في ١٧:٠١

آخر تحديث لفهرس SkillsMP: ٩ نوفمبر ٢٠٢٦ في ١٤:٢٢

skills مجمعة: ١

نجوم GitHub: ٠
تفرعات GitHub: ٠

التثبيت بمساعدة مساعد ذكي

انسخ هذا الطلب إلى المساعد الذكي الذي تستخدمه.

Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/SAP-samples/asug-handson.

ملف README للمستودع

مصدر ملف README للمستودع: README.md

قراءة الملف الأصلي

عرض ملف README كاملًا

# Architecture Center - Enrich your agents with context [![REUSE status](https://api.reuse.software/badge/github.com/SAP-samples/asug-tech-connect-architecture-center)](https://api.reuse.software/info/github.com/SAP-samples/asug-tech-connect-architecture-center) ## Description This repository contains the material for the ASUG Tech Connect 2026 session Architecture Center, North Star and AI Golden Path. In this hands-on session you build an end-to-end modern SAP data stack scenario: you take governed SAP S/4HANA data products from SAP Business Data Cloud (BDC) — sales orders, purchase orders, and customer master, plus a manufacturing track — refine them into golden records using layered SQL views in Dremio, build an ontology layer including non-SAP data, and finally ground a Joule agent on the result. ## Overview The primary scenario resolves a non-SAP CRM to governed SAP customers and proves the churn ↔ delivery link: *"are our at-risk renewals driven by our own delivery performance?"* — built by resolving messy CRM account names to SAP customer numbers, rolling SAP sales lines up to a per-customer on-time-in-full (OTIF) truth, and joining CRM cases and renewals into one golden account record. A manufacturing production-risk record is kept as an optional advanced exercise. You unify everything with data-product-centric ELT — not classic extract-and-duplicate ETL — and put a trustworthy AI agent on top. The stack: | Layer | Product | Role | | --- | --- | --- | | SAP data | SAP Business Data Cloud (BDC) | Governed SAP S/4HANA data products shared zero-copy | | Lakehouse + transformation | Dremio | ELT + semantic layer: medallion as layered SQL views, accelerated by reflections | | AI / agents | Joule | Agent grounded on the golden CRM 360 record (via ontology) | | Open storage | Apache Iceberg on Amazon S3 | Non-SAP CRM data, queried in place | > Terminology note: there is no new brand name for "ETL" here. The deliberate framing is data-product engineering on an open lakehouse (zero-copy ELT) — transformation as semantics (SQL views + reflections), not pipeline jobs. The movement primitives you will hear named in the tooling are replication flows and transformation flows. ## The data All data you need is already provisioned in Dremio for the session — you query it there, you don't download or load anything. The SAP tables resolve under `"teched_labs_sandbox"."sap_dp".*` and the non-SAP CRM under `"teched_labs_sandbox"."non_sap".*`; each exercise tells you exactly which objects to use. ## Requirements - Access to the lab tenant for SAP Business Data Cloud, Dremio, and Joule (credentials provided at the session). - A modern browser. No local installation required — all tools are browser-based. - Basic familiarity with SQL is helpful but not required; all queries are provided. ## Exercises - [Exercise 1 - Build the Golden Records in Dremio](exercises/ex1/) - [Exercise 1.1 - Resolve a non-SAP CRM to SAP customers](exercises/ex1#exercise-11-resolve-a-non-sap-crm-to-sap-customers) - [Exercise 1.2 - Build & materialize the CRM 360 golden record](exercises/ex1#exercise-12-build--materialize-the-crm-360-golden-record) - [Optional (Advanced) - OTIF manufacturing medallion](exercises/ex1/optional/) - [Exercise 2 - Ontologies on the Golden Record](exercises/ex2/) - [Exercise 3 - Build a Joule Skill on the Golden Record](exercises/ex3/) - [Exercise 3.1 - Import and enable the skill](exercises/ex3#exercise-31-import-and-enable-the-skill) - [Exercise 3.2 - Ask the skill churn & delivery questions](exercises/ex3#exercise-32-ask-the-skill-churn--delivery-questions) ## Contributing Please read the [CONTRIBUTING.md](./CONTRIBUTING.md) to understand the contribution guidelines. ## Code of Conduct Please read the [SAP Open Source Code of Conduct](https://github.com/SAP-samples/.github/blob/main/CODE_OF_CONDUCT.md). ## How to obtain support Support for the content in this repository is available during the actual time of the online session for which this content has been designed. Otherwise, you may request support via the [Issues](../../issues) tab. ## License Copyright (20xx-)20xx SAP SE or an SAP affiliate company and Architecture Center contributors. Please see our [LICENSE](LICENSE) for copyright and license information. Detailed information including third-party components and their licensing/copyright information is available [via the REUSE tool](https://api.reuse.software/info/github.com/SAP-samples/asug-tech-connect-architecture-center).

جارٍ تحميل ملف README للمستودع…

Skills في هذا المستودع

التصنيف قيد الانتظار

skill

المهنة

الوصف

آخر تحديث

ontology-manager-skill

غير مصنف

Fast, accurate ontology assistant for the SAP Ontology Manager. Answers questions, runs SPARQL queries, and triggers business actions — grounding every answer strictly in retrieved data. Fetches the RDF/XML schema once and writes SPARQL directly from it. Use…

لغة النص الأصلي: الإنجليزية

2026-10-26

عرض ١ من أصل ١ skills مجمعة.