sap-btp-cias

SAP Datasphere development skill with 3 specialized agents, 5 slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections, managing spaces and users, implementing data access controls, or using the datasphere CLI. Covers Data Builder, Business Builder, analytic models, 40+ connection types, real-time replication, task chains, content transport, and data marketplace.

This skill should be used when developing SAP Analytics Cloud (SAC) planning applications, including building planning-enabled stories, analytics designer applications with planning functionality, data actions, multi actions, version management, and planning workflows. Use when creating planning models, implementing data entry forms, configuring spreading/distribution/allocation, setting up data locking, building calendar-based planning processes with approval workflows, writing JavaScript scripts for planning automation, using the getPlanning() API, PlanningModel API, or DataSource API for planning scenarios, troubleshooting planning performance issues, integrating predictive forecasting into planning workflows, implementing Seamless Planning with SAP Datasphere, configuring BPC live connections for BW on HANA integration, building value driver trees for what-if analysis, or debugging data actions with tracing.

Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Llama, Gemini, Mistral), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.

SAP BTP Connectivity skill covering Destination Service, Connectivity Service, Cloud Connector, Connectivity Proxy, and Transparent Proxy for Kubernetes. Use when configuring destinations (HTTP, RFC, LDAP, MAIL, TCP), setting up cloud-to-on-premise connectivity, implementing OAuth and principal propagation, deploying connectivity proxies in Kubernetes/Kyma, troubleshooting connectivity errors (405, 407, 503), or configuring multitenancy.

SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage