With a new year ahead, it is a good moment to look back on one of SAP’s most significant announcements of the past year: Business Data Cloud (BDC). Introduced in February 2025, BDC came with an ambitious promise , seamless integration of data from source systems through Data Products, combined with the ability to share this data with (SAP) Databricks for advanced analytics and AI use cases, alongside non-SAP data.
Expectations were understandably high. As with most major platform announcements, however, it takes time before functionality becomes broadly available. Only in November 2025 did the Partner Test, Demo, and Development (TDD) system become available. Until then, partners such as Expertum had to rely on SAP’s documentation and early field experience with pioneering customers.
One year on, it is worth reflecting on what has been delivered, what works well, and where challenges remain.
Data Products: The Cornerstone of BDC
A central pillar of Business Data Cloud is the concept of Data Products, which SAP defines as reusable, curated data assets designed to support business use cases. SAP distinguishes between two types:
- Standard Data Products, maintained by SAP
- Custom Data Products, maintained by the customer
Standard Data Products
SAP uses several technologies to extract data from source systems and expose it as Standard Data Products. For S/4HANA-related content, standard CDS views are leveraged; in other cases, OData services or APIs are used. SAP takes responsibility for maintaining these models and ensuring compatibility with future releases.
SAP has stated that by default, Data Products will not include any specific ‘Z-fields’. However, if a customer onboards a (Custom) Data Product through BDC’s Foundation Services, the metadata for the source views is analyzed and subsequently harmonized with the Data Product in SAP Datasphere, enabling it to retrieve the contents of custom fields as of that moment. So long story short; if you custom fields are part of the source object’s metadata definition at the time of the respective Data Product’s onboarding, you will be able to leverage these custom fields. Note that only installed Data Products (and thus, replicated data!) support this feature.
Standard Data Products are delivered as packages that also enable standard Intelligent Apps in SAP Analytics Cloud for specific Lines of Business (LoB). Custom fields are not carried over to Intelligent Applications that are delivered as SAP-managed content. Both Data Products and Intelligent Apps can be activated easily via the BDC Cockpit.
Custom Data Products
Customers can also create Custom Data Products using the same extraction technologies (for example, CDS views in S/4HANA). Unlike Standard Data Products, these do not go through the SAP Foundation Service. Instead, the data must first be loaded into SAP Datasphere and then exposed through a self-created data package and Data Product.
Integration with standard CDS views makes this surprisingly straightforward. In our own TDD environment, we were able to create Custom Data Products in just a few clicks , a clear strength of the platform.
Availability and Coverage
At the time of writing, SAP lists 259 generally available Standard Data Products. While this may sound impressive, most of these products focus on master data. Currently, only three source systems are supported:
- S/4HANA Private Edition
- S/4HANA Public Edition
- SuccessFactors
This is not unexpected, as these systems already have strong integration with SAP Datasphere.
That said, there are some inconsistencies. Although SuccessFactors is listed as a supported source system, only the LoBs Finance, Supply Chain, and Sustainability are mentioned , none of which directly align with SuccessFactors. This suggests that SAP still has work to do when it comes to metadata consistency and clarity.
Delta Share and Databricks Integration
With the introduction of BDC, SAP also enabled integration with (SAP) Databricks via Delta Sharing. Using a zero-copy mechanism, Databricks can connect directly to data stored in the BDC object store.
If customers use their own Databricks environment, an additional BDC Connect license is required. SAP has since clarified that “zero copy” truly means zero copy: extracting SAP data into an external data warehouse is not permitted.
For many organizations, this was a disappointment. Numerous AI and advanced analytics use cases rely on enriching SAP data with non-SAP data inside an existing, non-SAP Databricks environment. Currently, it remains unclear under which conditions data may be copied , for example, whether transforming a Data Product sufficiently would qualify it as “own” data.
On a positive note, SAP has announced upcoming integrations with other data platforms, including:
- Google BigQuery
- Snowflake (planned for Q1 2026)
- Microsoft Fabric (planned for H2 2026)
These integrations will make it easier to combine SAP and non-SAP data in non-SAP data warehousing solutions.
Pricing Model: An Important Consideration
While SAP prominently highlights the availability of Standard Data Products, the pricing model is less visible and deserves careful attention.
Standard Data Products are licensed per Line of Business (e.g., Finance, Supply Chain). Pricing is based on the number of Full Use Equivalents (FUEs) in the source system, which determines the required Core Enterprise Analytics Capacity Units. These costs are in addition to the base BDC system setup and are not reflected in the BDC Capacity Unit Calculator.
Custom Data Products follow a different model. They require a fixed cost of 1,500 Capacity Units (CU) per month, of which 1,000 CU can be reused for other BDC components such as SAP Analytics Cloud or Datasphere. Effectively, this results in an incremental cost of around 500 CU per month, making Custom Data Products a significantly more cost-effective option in many scenarios.
Promises Made, Promises Kept?
SAP’s roadmap provides visibility into upcoming Standard Data Products, including content for the C4C suite. However, systems such as Ariba and IBP, which are currently more challenging to integrate into the SAP analytics landscape, are notably absent from near-term plans.
This is a missed opportunity. It is precisely these systems where Standard Data Products could deliver the most value compared to customer-built alternatives.
Another frequently cited benefit of Data Products is that they are semantically rich. This is true as long as the data remains within the BDC environment, where both business and technical names are visible.
However, the underlying storage format is Parquet, which does not retain business semantics. As soon as Data Products are consumed outside BDC , for example in Databricks , the business context is lost, leaving only technical field names.
Conclusion
Much has changed since the initial announcement of Business Data Cloud. SAP continues to invest heavily in the platform, and more customers are actively exploring its potential. Migration options are becoming available, including the re-wiring of existing SAP Datasphere and SAP Analytics Cloud environments, as well as moving BW systems to the cloud.
That said, Standard Data Products still require significant expansion, especially given their associated costs. Their suitability strongly depends on specific use cases and on whether all required Data Products are available , and fit for purpose , since they cannot be modified.
For organizations that want to remain close to standard SAP and limit custom development, Standard Data Products can work well with relatively small teams. However, flexibility remains limited.
For customers seeking greater adaptability , especially those working primarily with S/4HANA Cloud or requiring Z-fields and custom logic , Custom Data Products are often the better alternative, both functionally and financially.
Once SAP starts delivering Standard Data Products for currently hard-to-integrate systems, Business Data Cloud may truly become the accelerator it promises to be.
If you would like to learn more about what Business Data Cloud can bring to your organization, explore licensing options, or see a real-life demo, feel free to reach out to our BI team.
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