Dear Christkind: My SAP Datasphere Wishlist
Christmas is just around the corner, and, like any hopeful kid, I have a wish list for Christmas Eve. Mine’s a little different, though—it’s about SAP Datasphere. After working with it across several projects, I’ve put together a set of features, enhancements, and clarifications I’d love to see. Datasphere has come a long way, and if you follow the “What’s New” sessions and the roadmap, you’ll know many exciting capabilities have shipped and even more are on the way.
Here’s my breakdown of what I’m wishing for:
Enable Replication Flow Initial and Delta for Task Chains
Today’s behavior
Replication Flows support three run modes:
- Initial: Load all data (currently the only mode usable in Task Chains)
- Initial and Delta: Run an initial load, then replicate only changes
- Delta: Replicate only changes after the flow starts
Why this matters
Data warehouses have load dependencies: “Load B only after C is up to date.” In Datasphere, that often means transforming targets only after the latest transactional data is available. You model this with Task Chains. But once you move to a delta process, you’re forced into fixed Delta intervals—which can drift. For example, start at 13:00 with a 24-hour interval; if extraction takes 5 minutes, the next attempt is at 13:05, and your window keeps creeping.
Wishlist 💫
Enable a single Replication Flow to run Initial and Delta and, after the initial finishes, allow Task Chains to control when subsequent delta runs occur. That would let us model dependencies precisely—very much like a classic delta DTP in BW. Dear Christkind, that’s the behavior I want and if not possible please stop the creep so we can build the rest of the task chain with reliable time dependency.
Full REST API Coverage (Parity with CLI)
Today’s behavior
We can manage artifacts with the CLI. There is REST support via SCIM and the Consumption API, and the roadmap mentions REST for Task Chains.
Why this matters
“CLI first” is powerful, but it’s harder to integrate consistently into enterprise automation landscapes than REST. We want integrated solutions—CI/CD, ITSM, scheduling, governance tooling—all of which talk REST natively.
Wishlist 💫
Bring API parity: everything possible via the CLI should also be available via REST. That’s the foundation for robust, composable automation.
Updated Currency Conversion Artefacts
Today’s behavior
Currency Conversion artifacts are delivered via Standard Integration and use Data Flows. Recently, a conversion feature to switch Data Flows to Replication Flows was released—underlining that Replication Flows are the recommended extraction path.
Wishlist 💫
Please refresh the delivered Currency Conversion content, so it aligns with the recommended approach and uses Replication Flows out of the box. So please also update your Currency Conversion extraction which is delivered to the tenants.
Production-Scoped Role Templates (with Finer Privileges)
Today’s behavior
In production, we want to minimize change permissions for stability and governance. The current privilege model (C=Create, R=Read, U=Update, D=Delete, E=Execute, M=Maintain, S=Share, Manage) often forces us to grant Update just to allow transports and deployments—opening the door to “quick fixes” in production that are transported later… or never.
Wishlist 💫
- Provide production-scoped role templates with least-privilege defaults.
- Offer finer-grained privileges (especially around deploy, transport, and save) so we can separate runtime operations from development changes.
- Publish clear guidelines for production hardening and governance patterns.
Clear Path to 3rd party Integration outside of Standard Connectors
Today’s landscape
When a system isn’t covered by a standard connection, we currently look at options like:
-
1. SAP Integration Suite
- Open Connectors
- Cloud Integration
- 2. Writing to the Open SQL schema via a custom service (e.g., on BTP)
- 3. Writing to an HDI container deployed in SAP Datasphere
- 4. Using (SAP) Databricks for certain scenarios
These vary widely in skills, complexity, infrastructure, and cost. For small-scale needs—integrating just a couple of services—Integration Suite can be overkill.
Wishlist 💫
Provide opinionated guidance for lightweight, cost-effective 3rd-party integrations: recommended patterns, reference architectures, and when to choose which option—especially for smaller footprints.
Hierarchy Creation and Maintenance in SAP Datasphere
Today’s behavior
In BW, we could not only extract hierarchies but also create and maintain them. Customers still ask for this, and many are reluctant to move maintenance back to the source.
Wishlist 💫
Introduce first-class hierarchy authoring and maintenance directly in Datasphere, alongside extracted hierarchies, to meet modeling and governance needs where source systems aren’t the right place for stewardship.
Unit Conversion for Custom Units
Today’s behavior
Since Q3 2025, the analytical model supports unit conversion via a standard dialog, along with standard tables (e.g., kg ↔ liters). However, many companies use custom units that require their own conversion factors. S/4HANA allows defining custom units and factors.
Wishlist 💫
Enable custom unit conversions in Datasphere so organizations can leverage their S/4HANA custom units and apply them seamlessly in analytical models.
Transparent Mapping of Consumption Units (and Monitoring)
This topic can turn into “The Nightmare Before Christmas.” We need clarity on how to size tenants properly and to make informed architectural decisions—especially around Object Store usage.
- Open questions we need answered in product docs & UI
- Which Replication Flows consume Data Integration Hours?
- For the Object Store configuration for example: What counts as Requests? What are they used for? How many will we need? Are there concrete benchmarks or back-of-the-envelope examples?
- Where exactly does each artifact’s consumption come from, and how do we monitor it end-to-end?
- …
Wishlist 💫
A transparent, unified consumption model with clear definitions, examples, and sizing guides.
Built-in monitoring that attributes consumption to artifacts, projects, and users—so we can manage and optimize with confidence.
Conclusion
Some items on this list may already be in motion; others probably have workarounds (please share them!). Requirements differ by project, of course. But everyone working daily with SAP Datasphere can feel the product’s momentum.
Dear Christkind 🎄, a few of these features — and even a roadmap entry or two — would make many of us very happy. After all, anticipation is half the fun.
Author: Christian Schilcher-Willi
Christian has been working as a Business Intelligence Consultant at ZPARTNER since 2020. He is specialized in advanced SAP BW/4HANA, HANA native modeling and SAP Datasphere solutions. Christian has a strong technical background in ABAP programming, AMDP transformations, Python-based data processing. He has worked in projects in various industries and developed solutions for complex data extraction, integration and modeling.