Introduction to Seamless Planning
Seamless Planning is a new integration paradigm between SAP Analytics Cloud (SAC) and SAP Datasphere that unifies planning logic with enterprise-grade data storage and governance. It allows SAC to remain the planning experience and calculation engine while Datasphere becomes the authoritative and governed persistence layer for plan data and master data. This means planning teams can reuse planning data across analytics, data transformation pipelines, and operational applications—without duplicating or exporting data outside of SAC. Modelers can build SAC planning models that physically store their transactional data and public dimensions inside Datasphere. They also have control over whether planning artifacts from SAC are exposed in Datasphere for reuse across Spaces or downstream analytic models.
Technical Architecture
Model Metadata & Planning Logic: Planning calculations, version management, and data actions remain defined inside SAC.Fact Data & Dimensions Stored in Datasphere: The planning model’s fact tables and public dimensions are persisted in Datasphere to enable governed reuse and enterprise distribution.Data Exposure from SAC to Datasphere: SAC can expose selected planning objects as read-only Datasphere artifacts, enabling modelers to use these objects in Data Builder or transform them into Analytical Models.
Key Benefits
Unified Planning Data: Centralized storage of plan facts and dimensions in Datasphere ensures consistency across systems and workflows.Direct Persistence to Datasphere: Changes made in SAC planning flows are instantly reflected in Datasphere fact tables—no manual exports required.Optimized SAC Resource Usage: Offloading data storage to Datasphere reduces SAC’s memory and storage footprint.Enterprise Reusability & Governance: Datasphere’s modeling and transformation extend to planning data, enabling secure and scalable reuse in the form of analytic models.
This approach eliminates data silos, reduces duplication, and empowers organizations to operationalize planning data across their digital landscape—while preserving SAC’s rich planning experience at the front end.
Prerequisites for Seamless Planning
Before configuring or deploying planning models from SAC to Datasphere, ensure the following system prerequisites are met.
SAC Tenant Must Be Running on SAP HANA CloudSAC must be provisioned on SAP HANA Cloud infrastructure.To verify: Navigate to System → About in SAC and confirm the HANA Cloud version is listed.This ensures compatibility with Datasphere’s storage and modeling architecture.
2. Tenant Co-Location and 1:1 Linkage
Both SAC and Datasphere tenants must reside in the same SAP data center region.A 1:1 tenant relationship is required—each SAC tenant must be linked to a single Datasphere tenant.This linkage enables SAC to persist planning data directly into Datasphere spaces.This can be done in System à Administration à Tenant Links in both SAP Analytics Cloud and SAP Datasphere.
3. Consistent Identity Provider (IdP) Configuration
It is strongly recommended that both tenants use the same SAML-based Identity Provider (IdP).This ensures consistent user identity mapping across SAC and Datasphere.
4. System Owner Credentials on Both Tenants
The tenant linkage process requires authentication using a system owner account on both SAC and Datasphere.This account must have administrative privileges to authorize cross-tenant integration.
5. User Role Assignment in Datasphere Space
SAC users who need to create, edit, or expose planning models must be granted appropriate space-level roles in Datasphere.Without these roles, SAC will not be able to write data or expose model objects to the designated Datasphere space.
If any of the above conditions are not met, then Datasphere will not appear as a selectable data storage location in SAC. The SAP Knowledge Base Article 3515100 highlights certain errors along with their corresponding workarounds.
Workflow for Seamless Planning
Create a New Model in SAC: While creating a new Model in SAC, there is an option available to specify the Data Storage Location as a Space within SAP Datasphere.
2. Configure Dimensions and Measures: The model created with Datasphere persistence layer is created as a Planning Measure based model by default and the data storage location is Datasphere Space as shown in model details.
3. Expose to Datasphere: There is also an additional option in the Model Details to expose the underlying fact table in the chosen Datasphere space. What gets created in Datasphere: When a SAC planning model is configured to store data in Datasphere:
4. What gets created in Datasphere: When a SAC planning model is configured to store data in Datasphere:
A Fact object (read-only) becomes visible in the Datasphere Space.A corresponding physical table (sap.sac.<GUID>) is created to store transactional planning data.Any public dimensions used in the model are created in Datasphere as dimension tables and remain shareable across Space.
5. Execute Planning scenarios in SAC: With the new model now exposed in Datasphere, key planning scenarios can continue to be executed within SAC exactly as before. Seamless Planning does not alter the way SAC planning processes run; it simply extends the option to persist and integrate data through Datasphere while maintaining the familiar SAC planning experience.
Create and Execute a Data Action: Develop a Data Action in SAC to update planning data. Once executed, publish the updated data back to Datasphere to ensure synchronization across platforms.Conduct Actual vs Plan Analysis: Utilize SAC’s analytical capabilities to compare actual performance against planned figures. This enables variance analysis and supports informed decision-making.Extend Modelling in Datasphere: Build custom calculations directly within SAP Datasphere using the exposed model. Create a dedicated view and Analytical Model on top of these calculations, then visualize the results seamlessly in SAC for enhanced planning insights.
Important Considerations
SAP is actively working to reduce the space dependency in future releases, for latest updates please refer the SAP Roadmap Explorer and the help guide.
Cross-Model Planning Constraints: Currently all models involved in cross-model planning operations—such as a data action, cross-model copy step must be in the same Datasphere space.Shared Public Dimensions: Sharing public dimensions across multiple models is only supported when both the models and the associated public dimensions are deployed within the same SAP Datasphere space. The same requirement applies to currency rate tables, which must reside in the same space to be referenced across models.Hierarchies: Hierarchies defined in SAP Analytics Cloud are not exposed to SAP Datasphere. If hierarchical structures are required for modeling or reporting, Datasphere modelers must reconstruct these hierarchies natively within Datasphere, ensuring alignment with the underlying data model and semantic layer.
Seamless Planning in BDC
SAP is introducing a unified enterprise planning paradigm through SAP Business Data Cloud (BDC). This represents the next stage in the evolution of Seamless Planning, where planning activities are connected, real-time, and driven by trusted operational data—eliminating the traditional “export, transform, and import” workflow. Because SAC and Datasphere are core components of BDC, seamless planning is highly relevant in this context and establishes the foundation for deep integration of planning data within the BDC environment. Looking ahead, BDC has the potential to further enrich seamless planning by:
Supporting planning-enabled insight applications that combine analytics with actionable planning workflows.Extending planning architectures to include platforms such as SAP Databricks.Enabling the consumption of data products directly within planning processes, ensuring governed, reusable, and scalable planning assets.
To understand Seamless Planning in context of Business Data Cloud, please refer to this blog.
Introduction to Seamless Planning Seamless Planning is a new integration paradigm between SAP Analytics Cloud (SAC) and SAP Datasphere that unifies planning logic with enterprise-grade data storage and governance. It allows SAC to remain the planning experience and calculation engine while Datasphere becomes the authoritative and governed persistence layer for plan data and master data. This means planning teams can reuse planning data across analytics, data transformation pipelines, and operational applications—without duplicating or exporting data outside of SAC. Modelers can build SAC planning models that physically store their transactional data and public dimensions inside Datasphere. They also have control over whether planning artifacts from SAC are exposed in Datasphere for reuse across Spaces or downstream analytic models.Technical ArchitectureModel Metadata & Planning Logic: Planning calculations, version management, and data actions remain defined inside SAC.Fact Data & Dimensions Stored in Datasphere: The planning model’s fact tables and public dimensions are persisted in Datasphere to enable governed reuse and enterprise distribution.Data Exposure from SAC to Datasphere: SAC can expose selected planning objects as read-only Datasphere artifacts, enabling modelers to use these objects in Data Builder or transform them into Analytical Models.Key BenefitsUnified Planning Data: Centralized storage of plan facts and dimensions in Datasphere ensures consistency across systems and workflows.Direct Persistence to Datasphere: Changes made in SAC planning flows are instantly reflected in Datasphere fact tables—no manual exports required.Optimized SAC Resource Usage: Offloading data storage to Datasphere reduces SAC’s memory and storage footprint.Enterprise Reusability & Governance: Datasphere’s modeling and transformation extend to planning data, enabling secure and scalable reuse in the form of analytic models.This approach eliminates data silos, reduces duplication, and empowers organizations to operationalize planning data across their digital landscape—while preserving SAC’s rich planning experience at the front end.Prerequisites for Seamless PlanningBefore configuring or deploying planning models from SAC to Datasphere, ensure the following system prerequisites are met.SAC Tenant Must Be Running on SAP HANA CloudSAC must be provisioned on SAP HANA Cloud infrastructure.To verify: Navigate to System → About in SAC and confirm the HANA Cloud version is listed.This ensures compatibility with Datasphere’s storage and modeling architecture. 2. Tenant Co-Location and 1:1 LinkageBoth SAC and Datasphere tenants must reside in the same SAP data center region.A 1:1 tenant relationship is required—each SAC tenant must be linked to a single Datasphere tenant.This linkage enables SAC to persist planning data directly into Datasphere spaces.This can be done in System à Administration à Tenant Links in both SAP Analytics Cloud and SAP Datasphere.3. Consistent Identity Provider (IdP) ConfigurationIt is strongly recommended that both tenants use the same SAML-based Identity Provider (IdP).This ensures consistent user identity mapping across SAC and Datasphere.4. System Owner Credentials on Both TenantsThe tenant linkage process requires authentication using a system owner account on both SAC and Datasphere.This account must have administrative privileges to authorize cross-tenant integration.5. User Role Assignment in Datasphere SpaceSAC users who need to create, edit, or expose planning models must be granted appropriate space-level roles in Datasphere.Without these roles, SAC will not be able to write data or expose model objects to the designated Datasphere space.If any of the above conditions are not met, then Datasphere will not appear as a selectable data storage location in SAC. The SAP Knowledge Base Article 3515100 highlights certain errors along with their corresponding workarounds.Workflow for Seamless PlanningCreate a New Model in SAC: While creating a new Model in SAC, there is an option available to specify the Data Storage Location as a Space within SAP Datasphere.2. Configure Dimensions and Measures: The model created with Datasphere persistence layer is created as a Planning Measure based model by default and the data storage location is Datasphere Space as shown in model details.3. Expose to Datasphere: There is also an additional option in the Model Details to expose the underlying fact table in the chosen Datasphere space. What gets created in Datasphere: When a SAC planning model is configured to store data in Datasphere:4. What gets created in Datasphere: When a SAC planning model is configured to store data in Datasphere:A Fact object (read-only) becomes visible in the Datasphere Space.A corresponding physical table (sap.sac.<GUID>) is created to store transactional planning data.Any public dimensions used in the model are created in Datasphere as dimension tables and remain shareable across Space.5. Execute Planning scenarios in SAC: With the new model now exposed in Datasphere, key planning scenarios can continue to be executed within SAC exactly as before. Seamless Planning does not alter the way SAC planning processes run; it simply extends the option to persist and integrate data through Datasphere while maintaining the familiar SAC planning experience.Create and Execute a Data Action: Develop a Data Action in SAC to update planning data. Once executed, publish the updated data back to Datasphere to ensure synchronization across platforms.Conduct Actual vs Plan Analysis: Utilize SAC’s analytical capabilities to compare actual performance against planned figures. This enables variance analysis and supports informed decision-making.Extend Modelling in Datasphere: Build custom calculations directly within SAP Datasphere using the exposed model. Create a dedicated view and Analytical Model on top of these calculations, then visualize the results seamlessly in SAC for enhanced planning insights.Important ConsiderationsSAP is actively working to reduce the space dependency in future releases, for latest updates please refer the SAP Roadmap Explorer and the help guide.Cross-Model Planning Constraints: Currently all models involved in cross-model planning operations—such as a data action, cross-model copy step must be in the same Datasphere space.Shared Public Dimensions: Sharing public dimensions across multiple models is only supported when both the models and the associated public dimensions are deployed within the same SAP Datasphere space. The same requirement applies to currency rate tables, which must reside in the same space to be referenced across models.Hierarchies: Hierarchies defined in SAP Analytics Cloud are not exposed to SAP Datasphere. If hierarchical structures are required for modeling or reporting, Datasphere modelers must reconstruct these hierarchies natively within Datasphere, ensuring alignment with the underlying data model and semantic layer.Seamless Planning in BDCSAP is introducing a unified enterprise planning paradigm through SAP Business Data Cloud (BDC). This represents the next stage in the evolution of Seamless Planning, where planning activities are connected, real-time, and driven by trusted operational data—eliminating the traditional “export, transform, and import” workflow. Because SAC and Datasphere are core components of BDC, seamless planning is highly relevant in this context and establishes the foundation for deep integration of planning data within the BDC environment. Looking ahead, BDC has the potential to further enrich seamless planning by:Supporting planning-enabled insight applications that combine analytics with actionable planning workflows.Extending planning architectures to include platforms such as SAP Databricks.Enabling the consumption of data products directly within planning processes, ensuring governed, reusable, and scalable planning assets.To understand Seamless Planning in context of Business Data Cloud, please refer to this blog. Read More Technology Blog Posts by SAP articles
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