{"ref":"content:teched-2026-da204","page":"/content/teched-2026-da204","json":"/content/teched-2026-da204.json","generated":"2026-10-26","drafted_with_ai":true,"entity":{"id":"teched-2026-da204","title":"Unlock predictive and generative AI with your data in SAP HANA Cloud","url":"https://www.sap.com/events/teched/berlin/flow/sap/te26/catalog/page/catalog/session/1785947150390001YDyB","content_type":"talk","published_on":"source:sap-teched","explains":["artifact:btp-hana-cloud","capability:predictive-models","capability:multi-model-data"],"summary":"The AI features SAP lists for [SAP HANA Cloud](artifact:btp-hana-cloud): the function libraries for tabular prediction and forecasting, where [predictive models](capability:predictive-models) run inside the database, the vector engine, the knowledge graph engine, which is [graph, spatial and document data](capability:multi-model-data) put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.","short":"Talk on the predictive and generative AI features of SAP HANA Cloud","offers":["concepts"],"sources":[{"url":"https://developers.sap.com/build/teched","title":"SAP TechEd 2026 session catalogue feed","checked":"2026-10-11"}],"drafted_with_ai":true,"provenance":{"discovered_via":[{"source":"source:sap-teched","channel":"build/teched"}],"first_seen":"2026-10-11"}},"readings":{"liveness":[{"label":"Checked against the source","tier":"unknown","evidence":"nobody has checked it"},{"label":"Source reachable","tier":"unknown","evidence":"not crawled"},{"label":"Age","tier":"unknown","evidence":"no publication date"}],"compatibility":[{"label":"Version","tier":"unknown","evidence":"no version declared"},{"label":"Moved since?","tier":"unknown","evidence":"no publication date to compare"},{"label":"Findings","tier":"good","evidence":"none flagged"}],"reach":[{"value":null,"unit":"views"},{"value":null,"unit":"comments"},{"value":null,"unit":"likes"}]},"signals":null,"series":null,"edges":{"authors":[]}}