A simple mental model for the course: move SAP BW safely into a private-cloud edition, expose BW assets as governed data products, then gradually shift innovation toward SAP Business Data Cloud, SAP Datasphere, SAP Databricks, SAP-managed data products, and modern planning.
The transformation is not “rewrite everything in the cloud tomorrow.” It is a controlled path that preserves BW value while opening BW data to a business data fabric, data mesh, AI/ML, and open ecosystem tools.
Reduce the BW footprint. Offload data that is no longer needed for reporting or late postings into the object store based on SAP HANA Data Lake Files. Then move eligible BW systems into SAP BW, private cloud edition in SAP Business Data Cloud.
Use the Data Product Generator to replicate BW InfoProvider data into SAP Datasphere local tables/files, then publish these tables as custom data products.
Share data products with SAP Databricks, SAP Snowflake, SAP Datasphere, and SAP Analytics Cloud. Replace selected BW use cases over time with SAP-managed data products, clean-core models, and modern planning.
The benefits combine continuity and innovation: keep existing BW investments, but make the data easier to share, cheaper to store, and more useful for AI/ML and cloud analytics.
The move is an “as-is” modernization route. Converting BW NetWeaver to BW/4HANA is not required before moving to SAP Business Data Cloud, though it can still be done later.
The Data Product Generator turns BW InfoProvider data into SAP Datasphere local tables/files. Those tables become the base for custom data products in SAP Business Data Cloud.
| Concept | Meaning | Key details from the course |
|---|---|---|
| Source types | BW objects exposed via ODP-BW | InfoObject, DSO, advanced DSO, InfoCube, CompositeProvider, MultiProvider, Query as InfoProvider. Hierarchies are not yet supported. |
| Extraction modes | How data is replicated | Full extraction loads a snapshot. Delta extraction loads initial data and then changes where supported by the object type and BW release. |
| Local table/file | Datasphere target artifact | Activation creates the table/file in an SAP BW space using SAP HANA Data Lake Files; running the subscription fills it. |
| Scenario Generator | Mass generation for complex BW models | In BW Modeling Tools, it collects top-level objects plus dependencies, builds a scenario tree, and generates/activates subscriptions while preserving relationships. |
| Scheduling | Automation of extraction + merge | Use BW process chains for data subscription runs and SAP Datasphere task chains for merge tasks; BW can trigger Datasphere task chains. |
| Transport | Lifecycle movement | Transportable subscriptions use TLOGO type DSUB, active state, package, and transport request. Legacy local SUBS can be migrated using RSDDS_DSUB_MIGRATION. |
Open each lesson card for a compact explanation of what matters and what to remember.
BDC lets companies keep BW investments while using object storage, managed access, data product delivery, zero-copy sharing, Datasphere modeling, and Databricks AI/ML.
The course frames the journey as Optimize → Modernize → Innovate. Optimize footprint and move; modernize by creating custom BW data products; innovate by sharing and replacing use cases over time.
Prepare BW by meeting release/database prerequisites, then move as-is. BW NetWeaver does not need to be converted to BW/4HANA first.
DPG creates, activates, runs, and monitors subscriptions on BW data. It supports full and delta extraction depending on BW object/release and uses ODP-BW as source type.
Admin configures OAuth, certificates, RFC destinations, SAP BW Datasphere spaces, and object-store connection. Multiple targets and performance settings are supported.
Use BW/4HANA Cockpit app Data Subscriptions or SAP GUI transaction RSDPS. Define source, target, extraction mode, selections, projections, and process-chain variant. Activation deploys the local table/file.
For complex BW models, Scenario Generator in BW Modeling Tools builds a dependency tree, avoids duplicate subscriptions, supports transport settings, and mass-generates subscriptions.
Running an activated subscription loads data to the local table/file. Success changes “Has Data” to Yes; data can be checked in SAP Datasphere Data Builder.
Automation combines BW process chains and Datasphere task chains: BW extracts to inbound buffer, then Datasphere merge task consolidates into the delta table.
Before the first run, more settings are editable. After the table/file is deployed and data exists, only description remains editable. Deletion in BW does not automatically delete the Datasphere local table/file.
Transportable subscriptions are DSUB objects in Active state assigned to package and transport request. Local SUBS subscriptions can be migrated using RSDDS_DSUB_MIGRATION.
In Datasphere Data Sharing Cockpit, create a data provider profile, choose Formations visibility, select local table/file(s), save Draft, then switch status to Listed. This creates Delta Share endpoint and ORD document.
Data products can be shared from the BDC catalog to SAP Databricks or consumed by creating a catalog from Delta Share. Data scientists use SQL/Python notebooks, then publish new delta shares back as data products.
The strategic shift is from BW objects at the center to business data products at the center. Keep BW where it is strong, but grow cloud-native data products, AI/ML, self-service, and open ecosystem use cases.
Use SAP-managed data products for greenfield/clean-core use cases. Use Datasphere artifacts when SAP content needs extension. For transitional cases, preserve historic BW data as custom data products and combine with managed data products.
For BPC planning transitions, SAP recommends Seamless Planning in BDC: SAC dashboards write entered planning values to local tables in Datasphere. Hybrid models can consume BPC and BW-based data products.
SAP points to RISE with SAP System Transition Workbench, architecture guidance, BW modernization partner/assessment resources, and SAP Road Map Explorer for Business Warehouse Modernization.
The course does not recommend a single replacement pattern for every BW model. It recommends a phased portfolio decision: keep what needs BW reliability, replace what benefits from cloud-native semantics, and use data products as the bridge.
For complex ABAP/BW transformations, regulated reporting, additive delta logic, and trusted financial/legal calculations.
Use DPG and Scenario Generator to preserve historic BW data or feed existing BW semantics into Datasphere/BDC.
Replace CompositeProviders and BW Queries with views, analytic models, data access controls, and SAC stories where suitable.
For clean-core domains like SuccessFactors or S/4HANA where SAP-managed data products and intelligent content are available.
From BW objects as the center of analytics to discoverable, governed business data products as the center.
It creates subscriptions that replicate BW InfoProvider data into SAP Datasphere local tables/files, which can then become custom data products.
It reduces manual work for complex BW models by collecting dependencies and generating multiple subscriptions consistently.
BW process chain runs the subscription; Datasphere task chain runs the merge task. BW can trigger the Datasphere task chain.
Preserve reliable BW logic while gradually moving cloud-suitable use cases to SAP-managed data products, Datasphere models, and open ecosystem tools.
System Transition Workbench, SAP architecture guidance, BW modernization assessment, partner resources, and Road Map Explorer.
SAP’s cloud environment for governed data products, Datasphere, Databricks integration, catalog, and business data fabric direction.
Private-cloud deployment path for BW NetWeaver/BW/4HANA in BDC, preserving BW features while connecting to cloud innovation.
Tool for creating, activating, running, and monitoring data subscriptions from BW to Datasphere local tables/files.
Definition that specifies BW source, target, extraction mode, projections, selections, and process-chain integration.
Datasphere artifact backed by SAP HANA Data Lake Files where replicated BW data lands.
Open sharing mechanism used to deliver data products to consumers such as SAP Databricks.
Open Resource Discovery metadata standard used for describing data products and their capabilities.
DSUB is transportable data subscription TLOGO type; SUBS is older local/non-transportable type.
Planning approach where SAC captures planning inputs and writes them to local tables in SAP Datasphere.