SAP Business Data Cloud and Datasphere News in May
May was one of those months where everything happened at once. SAPPHIRE Orlando brought a wave of announcements for SAP Business Data Cloud — platform direction, new integrations, and some big bets on enterprise AI. And while the conference was still in full swing, the product team kept shipping: two solid Datasphere releases packed with useful enhancements for data integration, modeling, and transport.
Below you'll find my top feature picks from the May releases, a summary of the key SAPPHIRE announcements, and the usual roundup of community blogs worth reading.
My top features in May
SAP Snowflake and BDC Connect for Snowflake
Two closely related announcements that mark a big step for the BDC open partner ecosystem.
SAP Snowflake is now generally available as a solution extension — Snowflake's AI/ML and advanced data engineering capabilities delivered directly through SAP. Full Snowflake Business Critical Edition, provisioned via SAP for Me, with zero-copy access to SAP data products out of the box.
BDC Connect for Snowflake adds bidirectional data sharing on AWS for customers already running Snowflake. Same enrollment approach as BDC Connect for Databricks — data products flow in both directions, business semantics and governance intact.
Run Replication Flows with Delta Load at Scheduled Times
Long-awaited. You can now schedule replication flows that use delta-enabled objects by setting Delta Load Run to “At Scheduled Time”. The flow processes all available delta records and completes cleanly after each run. No more workarounds.
Bulk Assignment of Schedule Owner for Task Chains
You can now assign a schedule owner to multiple task chains at once — no more one-by-one configuration. A small change with a big impact for anyone managing larger environments with many scheduled jobs.
Analyze the Lineage Graph of a View with Runtime Metrics
The Runtime Metrics tool now lets you analyze the full lineage graph of a view, including all underlying source objects — not just the view in isolation. Much clearer visibility into where performance bottlenecks actually live.
Transport Runtime Settings for Flows and Views
Transformation flow runtime settings — HANA run modes, batch configurations, Spark application settings — can now be included in transport packages. The same applies to view persistency runtime settings in the Data Integration Monitor. One transport, consistent behavior across dev, test, and production.
Variables in Analytic Models
When using an analytic model as a source for another analytic model, you can now customize its variables — rename them, change default values, use them in restricted measures and calculations in the consuming model. A real flexibility gain for anyone building layered analytic models.
SAP Analytics Cloud Q2 2026 — Top 5 Features
A quick look at the QRC2 2026 SAC release Orla_C put together a great video walkthrough covering the top 5:
- Asymmetric Reporting
- Composite Versioning
- Job Monitor Enhancements
- Decoupled Data Panel
- Recent & Favorites in open/save dialogs
➡️ Watch it here: https://www.youtube.com/watch?v=0U7xc_8WN2I
SAPPHIRE 2026
My personal highlight at SAPPHIRE Orlando 🌴
This year I had the privilege of opening the SAP Business Data Cloud track at SAPPHIRE Orlando with the introductory session on Monday — and the response was something I didn't expect.
The session ended up as the #1 most registered session at SAPPHIRE 2026 overall, with more than 1,800 sign-ups over two sessions. And a lot of them showed up in the room. I'm still a bit speechless. Humbled, and honestly — kind of proud.
Thank you to everyone who registered, attended, or just followed along from afar. The energy in that room made it feel like more than a tech talk.
What's New in SAP Business Data Cloud at SAPPHIRE
SAPPHIRE 2026 brought a wave of announcements for SAP Business Data Cloud. Here's a quick summary of what was announced.
SAP Business AI Platform — SAP BTP, SAP Business Data Cloud, and SAP Business Transformation Management are converging into a single unified platform for building, contextualizing, and governing enterprise AI. At its core sits the SAP Knowledge Graph, which maps business entities, processes, and relationships across your SAP landscape.
SAP HANA Cloud natively in BDC — HANA Cloud becomes a core component of BDC, adding a unified in-memory engine for transactional, analytical, and multi-model workloads — alongside the existing SAP Databricks and SAP Snowflake integrations.
MDG and Reltio in BDC — SAP Master Data Governance is now a component of BDC, ensuring data products are verified and governance-aligned. The Reltio acquisition is complete and will be brought directly into BDC as well, adding multi-domain master data management with AI-based entity resolution and Model Context Protocol support for multi-agent workflows.
Joule Agents in the data fabric — Data products, analytical models, and planning structures can be created through natural language. SAP Analytics Cloud story generation is part of this too.
BDC Connect for Amazon Athena — Bi-directional zero-copy integration between BDC and Amazon Athena, extending the existing Snowflake and Databricks integrations. General availability planned for H2 2026.
👉I covered all of this in a dedicated recap video
My favorite blogs in May
@GregBotticchio covers a genuinely useful new feature in SAP Analytics Cloud Q2 2026: the Asymmetric Reporting Layout lets you design tables where different sections follow different structures — actuals at monthly level, forecast from a cut-off date, budget at quarterly level — all in a single table, no workarounds, no duplicated objects. If you've ever built three separate tables just to answer one business question, this one's for you.
🔗 Asymmetric Reporting Layout
@yoramfriedman breaks down a structural problem that doesn't get talked about enough: the place where business context lives can't run agents, and the place that can run agents doesn't have the context. Using S/4HANA as the example, he shows how meaning — contract terms, credit history, priority rules, semantic layers — stays behind when you extract data to a generic lake. A sharp read that explains the core problem SAP Business Data Cloud is designed to solve.
🔗 The Catch-22 of Most Business AI
@Gaurish-Dessai announces something worth knowing about: a new advanced learning journey and certification for SAP Data Architects, covering data strategy for the agentic AI era, architectural frameworks like TOGAF and DAMA-DMBOK, and SAP BDC integrations with Databricks, Snowflake, Fabric, and BigQuery. If data architecture is your game, this is your next step.
🔗 New SAP Data Architecture Learning Journey & SAP Certified Data Architect Certification is now Live
@cecilysorenson covers the latest Discovery Center updates — including a dedicated SAP BDC Service Catalog with missions, roadmaps, and transparent pricing, plus an AI Maturity Calculator developed with IDC. One central place to go from initial BDC exploration to full adoption, with practical guidance for managing SAP and non-SAP data.
🔗 What's New in SAP Discovery Center: From Inspiration to Guidance
@kurzdo93 traces the evolution of enterprise data architecture from the data warehouse era through the Lakehouse to what's needed today: a knowledge core that gives AI agents the business context to actually act, not just answer. He uses SAP Business Data Cloud to show how lake storage, intelligent compute (HANA Cloud, Databricks, Snowflake), semantic data products, and Joule agents come together as a business data fabric. A well-structured read if you want to understand the architectural “why” behind BDC.
🔗 AI has outgrown legacy data architectures like SAP BW — is your stack ready to keep up?
More blogs about SAP BDC and Datasphere to check out 👇
Find more information and related blog posts on the topic pages for SAP Business Data Cloud and SAP Datasphere. Also check out the SAP Help for SAP Business Data Cloud and SAP Datasphere, including for troubleshooting and analysis guides, onboarding guides, and more.
