SAP Community - SAP BW/4HANA

The SAP BW Data Product Generator for SAP Business Data Cloud

2025-04-10T16:48:07.114000+02:00

Overview

SAP customers will be able to integrate their SAP BW data with SAP Business Data Cloud (BDC) easily with a new tool, planned to be released soon: the BW Data Product Generator (short BW DPG). The BW DPG allows you to easily replicate your BW InfoProvider data to the managed Object store (HDLFS) of the Datasphere tenant of your BDC system for further usage in data product generation and consumption in analytical/planning scenarios on top of the Datasphere/SAC stack and/or sharing with Databricks and other consumers. This replication can be done as onetime snapshot, using regular re-loads or with incremental delta updates, if the underlying BW InfoProviders support delta. It will be available for SAP BW 7.5 on HANA and SAP BW/4HANA systems subscribed as part of BDC and RISE.

Details

How to install the BW DPG and setup your BW system as part of the BDC landscape will be rolled out in a different channel (see SAP Note 3590400). Here we assume that this is already done and the connection between the BW system and the BDC landscape is created.

The BW DPG comes with an own editor in BW (SAP GUI in SAP BW and a Fiori UI in BW/4HANA). Here you start by creating a so-called subscription. For a subscription you choose the InfoProviders that should be part of this replication package. You can select the relevant fields of the InfoProviders that should be replicated and can apply filter conditions to reduce the data to be transferred.

You can add the subscription as a process to a process chain, e.g. to orchestrate the update of the data in BDC right after the data has been updated in your BW system or to do the replication at a time of little load in your BW system to minimize any impact.

For each InfoProvider in a subscription a LocalTable (File) is created in a dedicated BW space of the Datasphere tenant. The data of the InfoProvider is materialized in this LocalTable (File) every time the subscription is executed.

The LocalTable (File) contains the basic metadata of the InfoProvider like data types, descriptions and field names. It can now be used as any LocalTable in Datasphere for further modeling. And you can use the LocalTables and easily create a DataProduct in the Datasphere Data Sharing Cockpit.

Usage Scenarios

New consumption

The main use case for the BW DPG is to quickly enable new consumption scenarios based on your BW data. Most prominent in the context of BDC is of course the zero-copy consumption of your BW data in Databricks. With a Data Product on top of the LocalTable (File) you can share the Delta Table of the Local Table (File) via DeltaShare with Databricks allowing e.g. machine learning algorithms to be executed without moving the data outside of your BDC landscape.

Using the LocalTable (File) for analytic consumption is also possible. The LocalTable (File) in the BW space is then simply shared to a consumption space in Datasphere where you build Views and Analytic Models on top of them combining BW data and data coming from other sources including SAP-managed DataProducts. At query runtime the data is accessed via HANA Cloud SQL-on-file directly in the Objectstore.

BW scenario replacement

While the main use case for the BW DPG clearly is the quick and easy creation of new consumption scenarios on BW data, the BW DPG can also be leveraged as part of the overall BW Modernization path and help to move certain scenarios from BW to Datasphere. When it comes to replacing BW scenarios customers should always first look at the availability (and roadmap) of SAP-managed Data Products and SAP Apps that can replace this out-of-the-box. For legacy scenarios in your BW system, where the data is no longer changing and not needed for consumption in the BW stack, you can use the BW DPG to move this data to BDC-Datasphere and then delete it in your BW system. The copy in Datasphere Objectstore becomes the only source should the data be needed again.

Should you plan to replace a complete data flow in BW with the data integration capabilities of Datasphere the BW DPG can also be used to create the necessary persistency objects (LocalTable(File)) and do the initial load of the historic data. The new data flows in Datasphere would then combine the data of the BW DPG and the recent data.

Supported InfoProvider types

The following BW InfoProviders can be used in a subscription for the BW DPG:

Base Providers: InfoCubes, Datastore Objects (Classic and Advanced), InfoObjects (Masterdata)
Composite Provider, MultiProvider
Queries: Query-as-InfoProvider

Availability

The BW part of the BW Data Product Generator will be available as a SAP Note Transport-based Correction Instruction (TCI) that can be installed on the following BW releases and product versions:

SAP BW 7.50
SAP BW/4HANA 2021
SAP BW/4HANA 2023

For the avoidance of doubt, the usage of DPG is only permitted for ‘SAP Business Warehouse private cloud edition’ systems deployed in SAP's private cloud as stand-alone installations.

The parts of the end2end flow in Datasphere are planned (!) to be available as follows

SAP Datasphere Wave 8: data can be loaded to Datasphere using the new BW tool, the LocalTable(File) can be consumed in analytic scenarios
In a soon upcoming Wave for SAP Datasphere: the LocalTable(File) can be used to create a Data Product which can be shared to Databricks

Possible future enhancements

Mass object selection for complete scenarios (e.g. an InfoProvider and all its masterdata)
InfoArea hierarchy as folder structure in the BW space
Support of multiple BW spaces as target (to separate data via spaces)
BW Process Chain and Datasphere Task Chain integration

Please note that future items may be subject to change.

How to Configure Email Notifications in SAP BW Bridge

2025-04-15T23:19:55.568000+02:00

Almost every SAP BW or SAP BW/4HANA system employs process chains to manage data loads, activate requests, schedule housekeeping tasks, and more. In most of these systems, email alerts are set up to notify you when steps in process chains fail, start late, or run longer than expected. This guide will walk you through the process of configuring email notifications for process chains in SAP BW bridge.

Prerequisites

In SAP BW bridge, you need to provide your own SMTP server to send outbound emails. This server can be within your corporate network behind a firewall or publicly accessible on the internet. Since SAP BW bridge is a public cloud offering, using a publicly available SMTP server simplifies the configuration process. If your SMTP server is within your corporate network, you'll need to expose it to the internet, such as by configuring it in the Cloud Connector. For detailed instructions, refer to SAP Help. Note that mail destinations are not supported for BW bridge because a BW bridge system is not visible in your BTP account.

Configuration

First, create a communication system that represents the SMTP server.

Logon to your SAP BW Bridge Cockpit.
Under Communication Management, open the app Communication Systems.
Click New to create a new communication system.
Under Technical Data > General, maintain the host name and port of the SMTP server.
Switch on Cloud Connector only if the SMTP server is exposed to the Internet via SAP Cloud Connector.
Under Users for Outbound Communication, click + to add user and password that can be used by SAP BW bridge to logon to the SMTP server.
Save the new communication system.

Then, set up a communication arrangement for outbound emails.

Under Communication Management, open the app Communication Arrangements.
Click New to create a new communication arrangement.
Choose SAP_COM_0548 as communication scenario and enter a meaningful name for the communication arrangement.
As Communication System, choose the one you created before. The Outbound Communication section will automatically show the user configured in that system.
Make sure that the Service Status in Outbound Services is set to Active.

Next, choose the events and process chains for which you want to receive email notifications.

In the SAP BW Bridge Cockpit, click on your initials in the upper right corner and select Settings.
Under Subscriptions, switch to tab Process Chains and click on Send Dummy Notifications.
Close Settings and ensure that you have received a long list of notifications, such as 'A process chain run for chain %TESTNOTIF_VERY_LONG takes much too long'.
Click again on your initials and Sign Out.
Sign on again, click on your initials once more, open the Settings dialog and select Notifications. There, you can disable specific notification types, such as those for completed process chain runs.
Under Subscriptions, you can set up notifications for process chains that you have triggered. By clicking the + icon, you can optionally specify which process chains you want to receive notifications for.

We're almost there, but there's an important detail to consider. Process chains in BW bridge are scheduled for the technical user SAP_SYSTEM which does not have an email address. Your SMTP server will typically reject emails sent by SAP_SYSTEM since it lacks a valid sender mail address. However, you can easily set a default sender address by coding and running a small ABAP class.

Open BW Modeling Tools and logon to your ABAP Cloud project.
Right-click the project name and select New > ABAP Class.
In the New ABAP Class dialog, select a package, enter a name and description for the class, and add the interface IF_OO_ADT_CLASSRUN.
Select a transport request or create a new request.
Copy and paste the coding below.
Adapt the email address and the name of the default sender (in lines 23/24) and the allowed domain for email recipients (in line 27). Make sure to use a pattern for the allowed domain for email recipients, including the asterisk (*) as shown in the example above.
Activate the class.
Right-click your class and select Run As > ABAP Application (Console) or select your class and press F9. You should see the message "Configuration was saved" in the ABAP Console.
See SAP Help for additional details on how to configure outbound mails.

CLASS zcl_configure_outbound_mails DEFINITION
  PUBLIC
  FINAL
  CREATE PUBLIC .

  PUBLIC SECTION.
    INTERFACES if_oo_adt_classrun .
  PROTECTED SECTION.
  PRIVATE SECTION.
ENDCLASS.

CLASS zcl_configure_outbound_mails IMPLEMENTATION.

  METHOD if_oo_adt_classrun~main.

    DATA(config_instance) = cl_bcs_mail_system_config=>create_instance( ).

    TRY.
*       activate mail config options
        config_instance->set_address_check_active( iv_address_check_active = abap_true ).

*       set allowed domains for email senders
        config_instance->add_allowed_sender_domains( it_allowed_sender_domains = VALUE #( ( '*@mycompany.com' ) ) ).

*       set default sender mail address
        config_instance->modify_default_sender_address( iv_default_address = 'noreply+BWBridge@mycompany.com'
                                                        iv_default_name    = 'Default Sender' ).

*       set allowed domains for email recipients
        config_instance->add_allowed_recipient_domains( it_allowed_rec_domains = VALUE #( ( '*@mycompany.com' ) ) ).

      CATCH cx_bcs_mail_config INTO DATA(write_error).
        "handle exception
        out->write( 'Oops, something went wrong' ).
        RETURN.
    ENDTRY.

    out->write( 'Configuration was saved' ).

  ENDMETHOD.
ENDCLASS.

That's it! You're now ready to start receiving email notifications for process chains.

You can monitor outbound emails in the app Monitor Email Transmissions. Your business user needs the business role SAP_BR_ADMINISTRATOR to see this app.

The app shows failed or pending email transmissions. For failed email transmissions, you'll see the status code and the response which should give you a hint on the root cause of the failure.

You can also use the app to send a test mail.

I hope this guide helped clarify how to receive mail notifications in SAP BW bridge. If you have questions or insights to share, feel free to drop them in the comments!

Restricting the BW queries exposed to Microsoft Power BI from B4HANA system

2025-05-11T08:36:20.516000+02:00

By default, all of the queries in B4HANA are exposed when the Microsoft power bi user tries to connect to B4HANA system. Even though the user might have limited access, like only to certain Finance queries but when they connect to B4HANA system using power bi then all of the queries in the B4HANA system get exposed by default. Ideally, they will not be able to execute all those queries, but they will be able to see what are all queries available. Now we need to restrict the queries in a way that user could see only those that they have authorization in the B4HANA side. This way user has precise access and security is much guaranteed as he will not know what are all other queries exist.

To access the B4HANA queries from power bi we need to provide authorization to below BAPI via the Authorization Object S_RFC

BAPI_MDPROVIDER_GET_CATALOGS

now I have created a role, in the role authorization Object S_RFC has been added and I have assigned the BAPI

But this will not restrict the access and will expose all metadata of the queries when user try accessing the system from Power bi.

To achieve restriction, we have followed the below approach

* Enhance the BAPI with user defined enhancement points & then use the logic to get only those queries assigned to user via S_RS_COMP, S_RS_COMP1.

This way the restrictions will get implemented.

As I have analyzed there are no explicit enhancement points provided by SAP within the BAPI, also could not find any BADI from CL_EXITHANDLER for this BAPI. So decided to use modification assistant and create a user defined enhancement point and put my code. We could have used the implicit enhancement points too but advantage with modification assistance is that during upgrade it will pop up and suggest us to take care of the added code.

within the BAPI the code below exposes all infoprovider that have queries defined on top of them.

Now we will override this assignment, please see the below code added by me using modification assistant and I have created one enhancement point ZBW4_EP_CATELOG_01 which belongs to enhancement spot ZBW4_ES_CATELOG_01

below is the code snippet under my enhancement point, what is does it, read the incoming user name from system variable syst-uname, once the user is identified then it is easy for us to identify the queries assigned to the user. I have used the table agr_users (this table will contain all the roles assigned to user) and I have used another table agr_1251 (this table will contain all the individual authorization objects, assigned against the roles).We are only taking active role assignment as on date as well as removed the deleted authorization objects. The default catalogs assignment is cleared and we are populating the catalogs from our user defined internal table lt_user. This way the restriction is applied and works for all user.

We recently went live and it works hassle free.

ENHANCEMENT-POINT ZBW4_EP_CATELOG_01 SPOTS ZBW4_ES_CATELOG_01 STATIC .
*$*$-Start: ZBW4_EP_CATELOG_01------------------------------------------------------------------$*$*
ENHANCEMENT 1  ZBW4_EI_CATELOG_01.    "active version 
**********************************************************************************************************
*  Enhancement ID       : ZBW4_EI_CATELOG_01                                                             *
*  Authors Name         : 50010755(Lakshminarasimhan Narasimhamurthy)                                    *
*  BI Ehnc No.          : B*-2*-0****                                                                    *
*  Create Date          : 07/Mar/2025                                                                    *
*  Last Update          : 07/Mar/2025                                                                    *
*  Description          : This enhancement will control the infoprovider access to the power bi          *
*                         The user executing from power BI will be checked for his assigned roles        *
*                         based on the roles the InfoProviders assigned to them will be restricted       *
*--------------------------------------------------------------------------------------------------------*
*  Transport #: B**K922743
*--------------------------------------------------------------------------------------------------------*
*                         Change History
*--------------------------------------------------------------------------------------------------------*
*Req. #       |Date        |Developer                    |Description
*--------------------------------------------------------------------------------------------------------*
*--------------------------------------------------------------------------------------------------------*
    data la_cat_nam type bapi6110cat.

      select distinct uname, low
      into table (lt_user)
      from agr_1251 as aobj
      inner join
      agr_users as user
      on
      aobj~agr_name = user~agr_name
      and
      uname = -uname
      and
      ( object = 'S_RS_COMP' or object = 'S_RS_COMP1' )
      and
      field = 'RSINFOCUBE'
      and
      low <> '*'
      and
      to_dat >= -datum
      and
      deleted = ''.

      clear catalogs[].

      loop at lt_user into data(la_user).
        condense la_user-low no-gaps.
        la_cat_nam-cat_nam = la_user-low.
        append la_cat_nam to catalogs.
      endloop.
ENDENHANCEMENT.

SAP BDC for Dummies

2025-05-18T21:14:34.766000+02:00

In recent past, the enterprise data market has moved at a disruptive rate from the outside via new players like Databricks, Snowflake, and an endless barrage of buzzword-laden solutions like artificial intelligence.

Moreover, tackling non-SAP data has been a big missing piece for SAP’s solution till date.

SAP's Business Data Cloud announcement was one of the most ambitious in SAP’s history. It also raised a flurry of questions on SAP's data strategy, how existing investments fit in, and what this means for SAP Business AI. Time to dig into the top community questions.

What is SAP Business Data Cloud?

SAP BDC is a fully managed SaaS platform that integrates:

SAP Datasphere for data modelling and integration
SAP Analytics Cloud for analytics and planning
SAP Business Warehouse capabilities (private cloud edition only)
Managed Databricks for advanced data processing (with limited features)
Context-aware intelligent applications for AI-driven insights (SAP Joule & Databrick's Mosaic)

It also includes curated, business-ready data products from SAP’s line-of-business applications which will be fully managed by SAP. Custom Data products can be created by Copying the SAP provided Data products or creating the partner products from Scratch.

Why is SAP launching BDC Now?

AI and Data Convergence: The explosion of AI capabilities demands better data infrastructure. BDC is SAP’s answer to this convergence.
Enterprise Complexity: Businesses are more interconnected than ever. BDC helps manage this complexity by offering a holistic view of operations.
Competitive Pressure: Companies need real-time insights to stay ahead. BDC enables faster, smarter decision-making.
Cloud Maturity: Organizations are now more comfortable with cloud-first strategies, making the timing ideal for a cloud-native data platform

What problems does SAP BDC solve?

SAP Business Data Cloud (BDC) addresses several critical challenges that modern enterprises face in managing and leveraging their data. Here's a breakdown of the key problems it solves:

Data Fragmentation Across Systems

Problem: Enterprises often have data scattered across SAP systems, third-party applications, and data lakes, making it hard to get a unified view.

BDC Solution: It integrates data from SAP and non-SAP sources into a single, governed environment—eliminating silos and enabling holistic insights.

2. Complex and Costly Data Integration

Problem: Traditional data integration is time-consuming, expensive, and often requires heavy IT involvement.

BDC Solution: Offers pre-built connectors, semantic models, and business-context-aware data products that simplify and accelerate integration.

3. Poor AI and Analytics Readiness

Problem: AI models often fail due to poor data quality, lack of context, or disconnected data sources.

BDC Solution: Ensures high-quality, contextual, and business-ready data that’s ideal for training AI models and generating actionable insights.

4. Limited Access for Business Users

Problem: Business users rely heavily on IT for data access and reporting, slowing down decision-making.

BDC Solution: Empowers business users with self-service analytics, planning tools, and intuitive interfaces—reducing dependency on IT.

5. Governance and Compliance Risks

Problem: Managing data governance, lineage, and compliance across multiple platforms is complex and risky.

BDC Solution: Provides centralized governance, lineage tracking, and policy enforcement to ensure compliance and data trust.

6. Slow Innovation and Time-to-Value

Problem: Building new data-driven applications or insights takes too long due to fragmented tools and processes.

BDC Solution: Speeds up innovation with a unified platform that supports rapid development, testing, and deployment of data products and AI solutions.

Apart from these, data movement is another crucial issue. Customers don't have the same data strategy; experts don't even agree on whether AI data should be in the cloud, on the edge, or in some elaborate 'lakehouse' or 'AI speed layer.' For BDC to live up to its billing, it can't require customers to be moving their data all over the place.

What Are Data Products in SAP BDC?

In SAP Business Data Cloud (BDC), data products are curated, reusable, and governed datasets that are designed to be easily consumed by business users, analysts, and AI applications. They are a core concept in BDC’s data-as-a-product approach.

A data product in BDC is:

A packaged dataset with business context, metadata, and governance rules.
Built from SAP and non-SAP data sources.
Designed to be discoverable, shareable, and reusable across the organization.
Delivered with semantic meaning, so users understand what the data represents.

What Does "Zero Copy" Mean in BDC?

In traditional data architectures, sharing or analysing data often involves copying it from one system to another—which is time-consuming, costly, and introduces governance risks.

In BDC, "zero copy" means:

Data consumers (like analytics tools or AI models) can access data directly from its source.
There’s no need to replicate or move the data into another environment.
This is enabled through open protocols like Delta Sharing, which allow secure, performant access to data in-place

How It Works

Delta Sharing (from Databricks) is integrated into BDC.
It allows remote access to Delta Lake tables (stored as Parquet files with metadata) without copying them.
BDC uses this to serve curated data products to consumers while maintaining central governance and control.

Benefits of Zero Copy in BDC

Faster Access: No waiting for data to be moved or transformed.
Lower Costs: Reduces storage and compute costs by avoiding duplication.
Better Governance: Centralized control over data access and usage.
Real-Time Insights: Enables near real-time analytics and AI applications.

I hope this blog gave you a better understanding of SAP BDC now.

How SAP tackles the upcoming challenges with BDC remains to be seen.

Happy Learning.

Swati Gawade-Shingade.

Cognizant technology Solutions.

Sunset of BEx Tools in SAP BW - What You Need to Know Before October 2025

2025-05-20T14:45:44.756000+02:00

Introduction: Sunset of BEx Tools - A Critical Milestone by October 2025

IMPORTANT UPDATE (10/15/2025):

BEx Analyzer and BEx Precalculation will no longer be supported in mainstream maintenance and will enter customer-specific maintenance with limited support effective October 15, 2025. Under customer-specific maintenance, the processing of problems is customer-specific. This means that for known problems, the solution is still covered by the maintenance. However, the customer may have to pay for the expense of solving new problems not yet known to SAP. In addition, SAP may, at its own discretion, choose to provide fixes under special circumstances e.g. for selected security issues, or for any critical bug that may impact the migration to alternative tools. See SAP Note 3665993 for more details.

Although BEx Analyzer and BEx Precalculation will be in customer-specific maintenance from October 15, 2025, other BW BEx tools such as BEx QueryDesigner and BEx WebApplicationDesigner have no direct dependency to Microsoft Office and will continue to be supported as usual until 2030, including, with the availability of bug fixes for any new errors reported for BW 7.5, and with a .NET compatible version not higher than 4.8. Consequently, support for other BEx tools such as BEx QueryDesigner and BEx WebApplicationDesigner is provided with BW 7.50 until the end of maintenance of BW 7.5.

With the clock ticking toward October 14, 2025, the end of support for Microsoft Office 2016 and 2019 also signals the end of mainstream support for Excel-based SAP BEx tools like BEx Analyzer, BEx Workbooks, and BEx Broadcaster (Pre-calculation) by SAP. While some BEx components (BEx Query Designer, BEx WAD) will continue in maintenance mode until 2027 or 2030, the Excel-dependent tools face a end of mainstream maintenance and move into customer specific maintenance with limited support from October 15, 2025.

While many organizations are already moving forward with SAP Datasphere adoption or planning their SAP BW/4HANA conversion, those still operating on SAP BW 7.x must urgently assess their current BEx tool usage to avoid disruptions and ensure long-term supportability.

In this article, we break down:

What BEx tools are affected and when
How to check if your system still relies on BEx Tools approaching end of support
Available replacements like SAP Analysis for Office and SAP Analytics Cloud
SAP's mass conversion tools and services to ease your transition

For answers to the most frequently asked questions (FAQ) about the BEx tools sunset, check out the dedicated FAQ:

👉Sunset of BEx Tools – Frequently Asked Questions and Answers (FAQ)

Whether you have already started migrating or are still evaluating your next steps, this article will help you understand the risks, available options with existing BEx tools usage.

BEx Solutions Overview

SAP offers a range of BEx-related tools and components, each serving different roles in the reporting and analysis workflow. These solutions fall into two broad categories; those dependent on Microsoft Excel and those that are web-based or standalone.

BEx tools can be classified in two broader categories:

Excel-Dependent (Impacted by both BEx sunset and Office lifecycle)

BEx Analyzer
BEx Workbooks
BEx Broadcaster

Standalone/Web-Based (Independent of Office support)

BEx Query Designer
BEx Queries
BEx Web Application Designer

BEx tools that rely on Excel only work with specific versions of Microsoft Office. The last versions supported by BEx tools are Office 2016 and Office 2019. Since Microsoft's decision to stop supporting Office 2016 & 2019 versions by October 14, 2025, this poses a hard limit on the mainstream maintenance support timelines for the excel based BEx reporting tools as well, and after that BEx tools (BEx Analyzer, BEx Workbooks and BEx Precalculation) dependent on Excel will enter into customers-specific maintenace support by SAP from October 15, 2025.

BEx tools that don’t rely on Microsoft Office (i.e. BEx Query Designer, BEx Queries, BEx WAD) can still be used and supported until 2027 (standard support) or 2030 (extended support), in line with BW 7.50 maintenance timelines. These tools are now in maintenance-only mode, meaning SAP will only provide basic support for fixing issues in BW 7.5 with no new development, innovation or new features planned for these BEx tools.

BEx Tools – Supportability Overview

Following table provides the End of Support for the BEx related products based on SAP NetWeaver or BEx End of Life timelines:

Key References and Support Notes for BEx Transition

The End of mainstream support for BEx (excel based tools) is reinforced by external dependencies, such as Microsoft’s end of support for Office 2016 and 2019, which directly impacts the usability and security of BEx Analyzer and Workbooks and BEx Broadcaster. Excel depedent tools such as BEx Analyzer, BEx workbooks and BEx Pre-calculation server will enter into customers-specific maintenace support by SAP from October 15, 2025.

SAP has formally communicated the BEx sunset through multiple channels, including official SAP Notes and blogs dating back as early as 2016. The references below serve as key evidence points supporting the urgency and inevitability of moving to modern alternatives like SAP Analysis for Office (AO) or SAP Analytics Cloud (SAC):

Microsoft Support link - Microsoft will no longer provide technical support, bug fixes, or security fixes for Office 2016 and Office 2019 vulnerabilities which may be subsequently reported or discovered. This includes security updates which can help protect your PC from harmful viruses, spyware, and other malicious software
Announcements for BEx sunset was announced through the blog - Announced in 2016
SAP Note 2609031 - Sunset of BW Business Explorer (BEx) – Announced in 2018

Additional References:

SAP Note 3665993 - End of Mainstream maintenance and start of customer-specific maintenance for BEx Analyzer and BEx Precalculation w.e.f. Oct 15, 2025
SAP Note 1973324 - BEx support for Microsoft Office 365 - Client Excel 2013 and 2016
SAP Note 3474912 – BEx Query Designer support for BW 7.50
SAP Note 3590297 - SAP BW NetWeaver Cloud: Information about maintenance availability in private cloud editions
SAP Note 1995532 - BI 7.x tools - HW\SW requirements and Compatibility of Microsoft Operating Systems and Office Products

BEx Sunset Adoption Gaps

As part of SAP’s long-term strategy to modernize its business intelligence tooling landscape, the sunset of BEx (Business Explorer) tools has been formally announced, encouraging customers to transition to more advanced and supported alternatives such as SAP Analysis for Office (AO) and SAP Analytics Cloud (SAC).

However, many SAP BW 7.x customers are at varying stages of adoption readiness, and significant gaps remain in fully realizing this transition. We observed these customers in following categories:

Transition Planned but BEx Still in Use: BW 7.x customers who have already planned the transition from BEx tools to modern alternatives such as SAP Analysis for Office (AO) or SAP Analytics Cloud (SAC)
- Users have been informed about the BEx sunset through communication efforts like end-user trainings, replacement solutions and awareness sessions
- Despite these efforts, end users continue to use BEx tools (e.g., BEx Analyzer, BEx Workbooks) for their reporting activities
Unaware of BEx Sunset: BW 7.x customers who are not aware of the sunset of BEx tools.
- BEx continues to be the primary reporting tool for all business use cases, as users are not informed of alternative solutions or the transition roadmap

What SAP Products are impacted:

SAP BW 7.5 or lower: BEx Analyzer/Workbooks can be the primary reporting front-end for classic BW systems
Embedded BW (in SAP ECC or ERP): Even though Embedded BW is typically used for operational reporting, BEx Analyzer/Workbooks can still used in some implementations
SAP SCM (Supply Chain Management): SCM systems with APO or SNP modules often have their own BW instance or rely on Embedded BW

While BEx is closely associated with SAP BW, its footprint extends into nearly every corner of the SAP ecosystem i.e. from legacy CRM and SRM systems to industry-specific solutions like IS-U and IS-Retail. Any system with a BW component or an integration to BW for analytics could potentially be generating BEx usage worth monitoring.

How to identify the impact in SAP BW system:

There are few potential options to check it in the system or EWA if BEx Analyzer or BEx Broadcaster is still used in the SAP BW system:

Option 1:

The SAP EarlyWatch Alert (EWA) report is a proactive monitoring tool provided by SAP that delivers a comprehensive technical health check of your SAP system. It is part of SAP’s support offering and is typically generated weekly to help detect and prevent potential issues before they impact system performance or availability.

Check section “Frontend Distribution” in BW EarlyWatch Alert reports. This section provides an overview of BW query executions, segmented by frontend tools, for the period covered in the EarlyWatch Alert (EWA) report. The data is sourced from the RSDDSTAT_OLAP view in the BW system.

The availability and data for the section depends on the configuration of the EarlyWatch Alert report for BW system: e.g.

ACTION REQUIRED: If there are any entries in BEx Analyzer 7.x and/or BEx Broadcaster, it is critical to initiate remediation steps to mitigate the impact of BEx End of support

Note: The statistics in EarlyWatch Alert report are extracted from the RSDDSTAT_OLAP view. Accuracy of the data relies on the proper enablement and execution of detailed statistics collection through transaction RSDDSTAT in SAP BW system, which must be activated for Workbooks, Queries, and InfoProviders to capture the statistics.

Option 2:

If EarlyWatch alert is not activated, you can login to the BW Production system, and manually check BEx tool usage accessing transaction SE16, and table RSDDSTAT_OLAP:

For BEx Analyzer / Workbook usage:
- Use selection “BEX” as STEPTP field and “3200” as EVENTID.
- Number of entries > 0 show the usage of BEx Analyzer / Workbooks in the system.
For BEx Broadcaster usage:
- Use “14601”, “14611” and “14671” as EVENTID.
- Number of entries > 0 show the usage of BEx Broadcaster (Pre-calc server) in the system.

The USERID field in the results will identify which users are actively using BEx tools

ACTION REQUIRED: If there are any entries in either of the above cases, it is critical to initiate remediation steps to mitigate the impact of BEx end of support.

Additional Consideration: This analysis is not limited to standalone BW systems. You can also perform this check in SAP systems with the SAP_BW component, such as ECC, SCM, or CRM etc. While most customers leverage standalone BW for central reporting, embedded BW capabilities in source systems allow the creation and use of BEx queries locally; another area that must be assessed during BEx deprecation planning.

How can SAP Services help?

BEx Workbooks

To ensure continuity and supportability, all BEx Workbooks should be migrated to SAP Analysis for Microsoft Office (AO). For customers with only a few BEx Workbooks, a manual migration may be more practical.

For customers with a large number of BEx Workbooks, SAP offers a tool for Automated Mass Conversion Tool to accelerate and facilitate the conversion process from BEx (Analyzer) Workbooks to Analysis for Office Workbooks. The Automated Mass Conversion Tool is 6x to 8x faster than the manual conversion method, conversion of 100 Workbooks take around 5-6 Minutes, compared to at least 30 seconds per one workbook in case of manual conversion.

This service is available for both MaxAttention (Premium Engagement) and Professional Services customers, if you would like to request it or find out more about it please contact your Engagement Architect, Technical Quality Manager, Account Manager or you can reach out to us via the email:

SAP PremiumHubCoE_BExtoAO_Migration

BEx Broadcaster (Pre-calculation)

Unlike BEx Workbooks, which benefit from SAP’s Mass Conversion Tool for migration to Analysis for Office, BEx Broadcaster (Pre-calculation) presents a different challenge. There are following replacement options available:

SAP Analysis for Microsoft Office (AO) with Scheduling via BI Platform
SAP Analytics Cloud (SAC) Publication

There is no automated conversion tool available for migrating broadcasting scenarios to replacement alternatives. Customers must manually rebuild scheduling and distribution logic from scratch using supported replacement options.

Conclusion

While many customers have already transitioned to modern alternatives, there are customers who still rely on BEx tools particularly BEx Analyzer, BEx Workbooks and BEx Pre-calculatio server for critical reporting and scheduling needs. BEx Analyzer, BEx Workbooks and BEx Precalculation will no longer be supported in mainstream maintenance and will enter customer-specific maintenance effective October 15, 2025.

Organizations with a significant footprint of BEx Workbooks should be aware that migrating to SAP Analysis for Office can require substantial time and manual effort. SAP offers a Mass Conversion Tool and expert services through SAP MaxAttention and the CoE teams to accelerate this process and reduce the operational burden. Please connect at SAP PremiumHubCoE_BExtoAO_Migration.

For those using BEx Broadcaster (Pre-Calculation Server), it is equally important to plan a transition to supported scheduling solutions using manual rebuild such as SAP BusinessObjects BI Scheduling or SAP Analytics Cloud Publications.

Taking proactive steps today will ensure business continuity, reduce security and compliance risks, and set your organization on a clear path toward a modern, supported, and future-ready analytics strategy beyond BEx.

What exactly is SAP BW PCE… and what it is not !

2025-06-14T09:00:00.025000+02:00

Dear BW enthusiasts!
In February 2025, SAP announced SAP Business Data Cloud (BDC). Amongst others, it combines the strengths of SAP Datasphere, SAP Analytics Cloud and provides many innovations including a deep integration with SAP Databricks for ML and AI use cases. In addition, the term “BW Modernization” also plays a key role in this new environment.

This blog post is meant to clarify the product behind this term, which is sometimes referred to SAP BW[4] PCE. Other terms like RISE-BW, HEC, BW cloud private edition, BW tailored option, BW BDC, SAP BW NetWeaver Cloud private edition, or SAP Business Warehouse Cloud are sometimes used in this context as well and that altogether leads to a high level of confusion. So, if you feel the same – keep on reading…

So let’s start to define the term exactly: What is this SAP BW[4] PCE ?
PCE means private cloud edition and refers to a deployment in the SAP private cloud as opposed to on-premise deployments or deployments at 3rd party hosting/service partners.
BW[4] is an artificial umbrella term we at SAP like to use referring to both products equally: SAP NetWeaver BW 7.5 on HANA and SAP BW/4HANA. You surely know that both products are quite different in maintenance strategy and functional scope; but here the focus is not on features&functions, but on the private cloud deployment mode.
So, the image above means, that you are on SAP´s recommended BW modernization path if you run SAP BW 7.5 on HANA or SAP BW/4HANA in SAP´s private cloud.

What is SAP BW[4] PTO?
PTO stands for private cloud tailored option and refers specific infrastructure configuration in the private cloud deployment, e.g. CPU power, memory size, disc space, disaster recovery&backup concepts, SLAs just name some typical ones.
In standard PCE terms, this configuration is defined by the well-known T-shirt size approach concept. But if customer requirements cannot be covered there, a more specific approach can be designed in a “tailored option”.
So in a nutshell, PTO is a specific flavor of the SAP-managed private cloud model to meet individual customer needs regarding infrastructure. In commercial terms, standard PCE and PTO (and other...) approaches are quite different and result in completely different contracts.

What is SAP BW[4] PCE not?
Very clearly – SAP BW[4] PCE is not a new or revised product. It is not a new codeline.
It is the same codeline as BW on HANA or BW/4HANA on premise.
Also worth mentioning - it is not a public cloud solution.
Finally, it does not restrict any existing features. In terms of functionality SAP BW 7.5 on HANA PCE provides 100% of the features of SAP BW 7.5 on HANA. And SAP BW/4HANA covers the exact same scope as SAP BW/4HANA PCE of the same release and SP level.
Exception: The so-called Data Product Generator is available in PCE depoyments in BDC only – but what you currently use in SAP BW[4] on-premise is also available in BW[4] PCE.

How to get to SAP BW[4] PCE?
If your BW system is managed by SAP already, then you are there already: You leverage BW[4] PCE.
For all other customers: A technical migration is needed from the current data center to a Hyperscaler data center managed by SAP. This migration is sometimes referred to as “Lift&Shift”, because in most cases it is a 1:1 move without any changes to the database or the ABAP application stack. It comes with a downtime for each system tier and some testing effort with focus on interfaces rather than on internal BW processes of course, but expectation is generally that everything keeps working in PCE in a non-disruptive way.
If the system is currently running on a 3rd party database, a migration to SAP HANA is required, because PCE´s minimal requirements are BW 7.5 on HANA. You can also include a ABAP stack SP-update or release upgrade when moving to PCE.

SAP provides the RISE methodology including tools, concepts, processes, experts etc. to bring customer SAP-landscape into PCE. So, if customers sometimes refer to their “SAP RISE BW”, they actually mean BW[4] deployed in PCE after a successful RISE project delivered by SAP.

What is different with SAP BW[4] PCE in SAP Business Data Cloud?
If your SAP BW[4] PCE subscription includes SAP Business Data Cloud (BDC capacity units), you have currently one additional feature: The Data Product Generator which derives data products from SAP BW[4] PCE InfoProviders into the BDC Object Store of SAP Datasphere (HDLFS, SAP HANA Cloud Data Lake File System).
Based on this integration, customers can consume BW[4] data in 3rd party tools (like Databricks, Google BigQuery, Snowflake, MS Fabric) without additional data replication (bi-directional zero-copy consumption), combine your valuable BW[4] data with other data in SAP Datasphere/SAC and/or redesign relevant SAP BW[4] applications in BDC step-by-step to decommission SAP BW[4] in the medium term. SAP note 3590400 explains how to enable this additional function and SAP note 3584640 explains, that embedded BW scenarios are out of scope in general. Also refer to SAP BW/4HANA help portal.

What about system maintenance end dates?
One important value added of running BW 7.5 in PCE is the automatic maintenance extension of three years until end of 2030 with no additional fees. See SAP note 3590297 and the SAP Product Availability Matrix (PAM) for more details.

Summary
The purpose of this blog post is to explain the significance of a private cloud deployment for SAP BW or SAP BW/4HANA. We at SAP see this as the first crucial step towards a viable modernization shifting from classic BW data flows and BW queries towards Datasphere data models and reporting&planning in SAC. There are still open questions regarding the detailed modernization approach, and future publication will surely follow...
However, it should be clear, that the move into PCE based on a RISE migration project is a step into the right direction which finally ends in SAP Business Data Cloud including BW[4] PCE. In a nutshell:

Go through a RISE project to bring your BW landscape to an SAP-managed private cloud deployment.
Then, shift&expand BW scenarios to SAP BDC (Datasphere + SAC) step by step.
Finally, adopt SAP BDC completely and decommission SAP BW[4] PCE.

Let´s also emphasize once more, that we are talking of a technical migration only. A RISE project is a infrastructure shift + a quite huge commercial change + new operation model mainly. Shifting from PCE to BDC lateron is a pure a commercial adjustment but does not result in another technical migration project from a SAP BW perspective.

Same same - but different!
Another final message to you BW enthusiasts: Don´t be confused if one organization names it "HEC BW", another one "RISE BW", or others "PCE BW" , "BDC BW" etc... Most likely they are same same in terms of functionality - but they might be really different commercially!

Some useful notes

0052505 - Support after end of mainstream maintenance or extended maintenance
1648480 - Maintenance for SAP Business Suite 7 including SAP NetWeaver
2741041 - Maintenance for SAP NetWeaver 7.x Business Warehouse
2934895 - Maintenance for SAP BW/4HANA
3590297 - Information about maintenance availability in SAP BW private cloud editions
3590400 - Configuration SAP BW[4]: Data Product Generator for SAP Business Data Cloud
3584640 - Data Product Generator in embedded SAP BW in SAP ERP and S/4HANA
SAP BW/4HANA help > Integrating Data from the Data Product Generator for SAP Business Data Cloud

Thanks to Alex and Wim for sharing their thoughts...

Introducing the RISE with SAP System Transition Workbench

2025-06-19T14:59:08.710000+02:00

Embarking on the RISE with SAP journey to transition to a private cloud environment can be overwhelming, but with the RISE with SAP System Transition Workbench, you have a powerful ally at your disposal to support you with the technical procedures and make them nearly seamless. Developed collaboratively with SAP Enterprise Cloud Services, the workbench is a dedicated tool ensuring a standardized and automated path to the private cloud, irrespective of your preferred migration approach.

What is the RISE with SAP system transition workbench?

The RISE with SAP System Transition Workbench is designed to be an extension of the family of software logistics tools such as SWPM and SUM in the context of private cloud transitions. It builds upon their capabilities to provide a highly automated guided procedure from the start to the end of the technical transition process.

The RISE with SAP System Transition Workbench supports a growing portfolio of migration approaches, which can be used for all SAP NetWeaver-based on HANA target systems. Detailed documentation is available for each supported approach, providing clear guidelines and insights on how to proceed with your specific migration requirements.

At the time of writing, the following approaches are available, either generally or as part of out early adopter program

SAP HANA Tenant Copy
SAP HANA Backup and Recovery
Homogeneous "Update and Copy"
System Conversion using SUM 2.0 (DMO with System Move)
System Conversion using SUM 2.0 (DMOVE2S4)

Each migration approach is facilitated through a structured guided procedure, referred to as "a cockpit". This cockpit is meticulously crafted to guide users through the technical procedure and is split into two main phases: the uptime phase and the downtime phase. This structure ensures that users have a clear understanding and control over the entire process.

New approaches and improvements are continuously bringing added, and you can track the same in our release note, and documentation.

What are the key benefits?

Extensive automated pre-requisite check report per migration approach, engineered to considerably reduce manual effort in verifying the system readiness for the selected approach and ensuring that all necessary criteria are met in a timely manner, reducing unplanned delays in the project runtime.
Automation integrated into the workbench. This automation is crafted to significantly minimize the time spent and the errors occurred in manual steps of the process, like system preparation, configuration, validation, etc. Reducing the amount of manual steps results in a stable, efficient, reliable and repeatable migration.
Reduced post-processing timelines by SAP ECS. The workbench ensures a consistent with SAP ECS’s standard and expectations, state of the system at the time of handover, which substantially decreases the need for time consuming follow-up actions and corrections.

Who is it for?

The RISE with SAP system transition workbench is available to all customers transitioning into the private cloud, supported by their respective migration teams, whether they are qualifying partners or SAP directly. Access to the workbench is straightforward, as it comes pre-installed on the migration server designated for the migration purpose.

Staying Updated

Keeping the workbench up-to-date is easy. The latest version of the tool is maintained in the release note, and updates can be requested at any time through a service request in SAP for Me.

Your feedback matters

We value your input and are continuously working to improve the RISE with SAP System Transition Workbench. If you have any feedback or suggestions, please use the send feedback form in the tool or reach out to us directly.

Summary

The RISE with SAP System Transition Workbench is not just a tool - it's your navigation system in the digital transformation landscape. By radically reducing manual efforts, minimizing errors, and streamlining processes, it ensures that your journey to the private cloud is as smooth and efficient as possible. Check out our documentation and early adopter program and discover how you can leverage this incredible inovation to facilitate your migration endeavors.

Driving Authorization of a BW query in SAP BW/4HANA

2025-06-24T10:34:07.322000+02:00

Introduction

Driving authorization of a BW query in SAP BW/4HANA involves controlling which users can access which data while executing the query. It ensures that users can only view the data they’re allowed to see based on security and authorization settings. This is typically done using Authorization Objects, Analysis Authorizations, and InfoObject restrictions.

Before we get into this topic, I recommend checking out my previous blog where I explained the BEx query elements, which will help you better understanding this blog.

The main focus of this blog is to cover the scenarios that are commonly encountered with respect to Authorization of a BW queries.

How to identify which BW query/queries uses a specific authorization variable.
How to identify which BW query/queries uses a specific InfoObject in fixed filter section of a query?
Step-by-Step process to restrict BW Query Access by authorization relevant InfoObject.

Now let’s discuss one by one in detail.

How to identify which BW query/queries uses a specific authorization variable

Let's assume we have an authorization variable called "0A_COSTC". We need to identify which BW queries uses this specific variable. This can be achieved by correlating RSZCOMPDIR, RSZELTXREF & RSZRANGE tables in the backend. This approach will help us understand the impact on a BW queries if we make any changes to the Variable or the associated InfoObject.

Step 1: In the table RSZCOMPDIR, enter the authorization variable name in the field COMPID to obtain COMPUID of a authorization variable and execute the table.Screenshot 1 : Input to RSZCOMPDIR table

Step 2: In the table RSZRANGE, enter the COMPUID of the authorization variable (from Step 1) in the field LOW to obtain ELTUID and execute the table.Screenshot 3 : Input to RSZRANGE tableScreenshot 4: Output of RSZRANGE table

Step 3: In the table RSZELTXREF, enter ELTUID (from step 2) in the field TELTUID to obtain SELTUID and execute the table.Screenshot 5: Input to RSZELTXREF tableScreenshot 6 : output of RSZELTXREF table

Step 4: Again, in the table RSZELTXREF, enter SELTUID (from step 3, where LAYTP = ‘AGG’) in the field TELTUID to obtain SELTUID and execute the tableScreenshot 7: Input to RSZELTXREFScreenshot 8: Output of RSZELTXREF table

Step 5: In the table RSZCOMPDIR, enter SELTUID (from step 4, where LAYTP = ‘SOB’) in the field COMPUID to obtain BW query/queries list in which Authorization variable is used.Screenshot 9: Input to RSZCOMPDIR tableScreenshot 10: Output of RSZCOMPDIR table

Note: In step 5, we obtained the list of queries where the authorization (processing type) variable was used. Follow the same procedure to identify other type of variables used in BEx queries.

2. How to identify which BW query/queries uses a specific InfoObject in fixed filter section of a BW query

In BW queries, the Fixed Filter section is used to restrict data at the query level, meaning the filter is always applied and cannot be changed during query execution. Often, specific InfoObjects like Company Code, Cost Center or Region are used here to limit the data scope for reporting or security purposes.

For Example, let's say we have an InfoObject called "0COMP_CODE". This InfoObject might be used in the Fixed Filter section of certain BW queries to ensure that only data related to a specific company code is included in the report. If we plan to delete, rename, or change the behavior of the "0COMP_CODE" InfoObject, it is crucial to understand which queries will be affected.

Step 1: In the table RSZRANZE, enter InfoObject name in the field IOBJNM to obtain ELTUID and execute table. Screenshot 11: Input to RSZRANGE tableScreenshot 12: Output of RSZRANGE table

Step 2: In the table RSZELTXREF, enter ELTUID (from step 1) in the field TELTUID to obtain SELTUID and execute the table.Screenshot 13: Input to RSZELTXREF tableScreenshot 14: Output of RSZELTXREF table

Step 3: Again, in the table RSZELTXREF, enter SELTUID (from step 2, where LAYTP = ‘AGG’) in the field TELTUID to obtain SELTUID and execute the table.Screenshot 15: Input to RSZELTXREF tableScreenshot 16: Output of RSZELTXREF table

Step 4: In the table RSZCOMPDIR, enter SELTUID (from step 3, where LAYTP = ‘SOB’) in the field COMPUID to obtain BW query/queries list in which specific InfoObject is used.Screenshot 17: Input to RSZCOMPDIR tableScreenshot 18: Output of RSZCOMPDIR table

Note: In step 4, we obtained the list of queries where the 0COMP_CODE InfoObject was used. Follow the same procedure to identify other InfoObjects used in BW queries.

3. Step by step process to restrict BW query access by authorization relevant InfoObject

In most business scenarios, Company code is a critical organizational element used to separate financial data within an enterprise. To ensure data security and compliance, it is often necessary to restrict users access to BW queries based on their authorized company codes. This prevents users from viewing financial data for companies they are not responsible for or permitted to access.

For example, if a user is authorized to access only company code 1000, they should not be able to view reports that include data from company code 2000 or others. SAP BW enables such security control through the use of authorization objects, authorization variables and analysis authorizations (RSECADMIN).

By following a structured step by step process, we can ensure that users only see data relevant to their roles, thereby enforcing data-level security in BW reporting.

Step 1: Identify the InfoObject for Company Code

Usually, the InfoObject for Company Code is 0COMP_CODE.
Ensure this InfoObject is marked as authorization-relevant in its properties.

Screenshot 19: Display of InfoObject 0COMP_CODE

Step 2: Create or Maintain an Authorization variable

Go to HANA Studio and create a new authorization variable on 0COMP_CODE.
- Example Variable: ZV_COMP_CODE
- Processing Type: Authorization
- Variable Represents: Single Value/Multiple values
- Ready for Input: Optional (Depending on your use case)

GIF File: Creating variable

Step 3: Insert the Authorization Variable in BW Query Filter

Open Your BW Query in the HANA Studio.
In the Fixed Filter section, drag the Company code InfoObject.
Assign the Created Authorization variable (ZV_COMP_CODE) as the filter value.
This ensures the query filters Company Code values based on the User's authorizations.

Screenshot 20: Displaying Query with restriction on 0COMP_CODE in HANA studio

Step 4 : Maintain Analysis Authorizations

Go to Transaction : RSECADMIN.
Under the Authorizations tab, create or modify an authorization object.
- Include InfoObject 0COMP_CODE with appropriate values (e.g., 1000, 2000, 3000).
- Use Value "*" if access to all company codes is allowed.
Assign the authorization object to the user or role under the User tab.

Screenshot 21: Initial screen of RSECADMIN T-code

Step 5: Test with Different Users

Log in with different user IDs having different Company Code authorizations.
Run the BW query and verify that each user sees only the data for authorized Company Codes.

SAP BDC Ecosystem

2025-07-09T23:04:37.578000+02:00

By now you may have got a good understanding of SAP BDC components from my earlier blogs.

Now let's try to see how it all fits together.

At the first level we start with the data repository source. It may be an SAP system (like SAP S/4, Success Factor, SAP BW etc. ) or any non-SAP system.

Customers struggle a lot in heterogeneous system where data is stored in multiple different data storage systems. This data is vital for reporting.

For the data-driven modern organisations, having convenient access to all the necessary data in a specific and centralised location is important. Easy, convenient access ensures that data resources are always available at a moment’s notice, easing the process for you and allowing you to conduct all operations.

With SAP BDC, various in-built SAP provided connectors available which we can use to connect to SAP as well as non-SAP systems and integrate them as a source of information i.e. transactional & master data.

SAP BDC system resides in SAP BTP platform similar to SAP Datasphere tenant sub-accounts currently.

You will have a separate SAP Datasphere instance inside your SAP BDC environment.

SAP Datasphere is the evolution of the SAP data warehouse(earlier SAP BW) solution in the cloud, combining capabilities from SAP Data Warehouse Cloud with its agile enterprise data warehouse, self-service data modelling and SAP Data Intelligence Cloud with its data orchestration, lineage, quality, among other capabilities.

In data integration projects, a lot of time is spent trying to recreate context that has been lost during data replication, especially when getting data from the database layer belonging to heterogeneous storage systems.

With SAP BDC, customers will be able to bring all the structured and non-structured data under single umbrella in business data fabric.

This simplifies complex data landscapes and delivers meaningful data to every data consumer, be it Data architect, business user or a decision maker – it takes the benefits and value further by keeping the business logic and application context from data intact.

For each of the source systems, SAP has provided ready-to-use data products which can be found in SAP BDC Cockpit.

To use out-of-the-box Data Products in SAP Business Data Cloud with third-party data, first browse the available Data Products in the SAP Business Data Cloud Cockpit. Then select and install the one that best meets your requirements before proceeding with integration.

SAP BDC system eliminates the need to recreate all the business context lost from extracting data - giving business stakeholders and data consumers the ability to accelerate their decision-making with trust and confidence, knowing they always have the complete picture of their data regardless of where it is stored or how it was designed.

SAP Data products are combination of curated views & tables, metadata, access control, inbound and outbound interfaces, load capabilities, data lineage etc. which are used by semantic layer in SAP Datasphere by consumption ready data models which can be then used for internal data manipulation and transformation.

This data can then be used for

Reporting by SAP Analytics cloud through live data, dashboards and stories
AI/ML capabilities by Databricks for powerful compute and advance analytics
Visualization by intelligent apps for business users to interact with real-time insights securely and intuitively

SAP BDC replicates source data into Datasphere object store once; downstream consumers access it from there.

With use of delta Sharing , Databricks gets real-time access to data without duplication saving storage space and associated costs.

All in all, SAP BDC is built upon a robust stack of integrated components, each playing a vital role in its functionality.

SAP BDC combines SAP Datasphere, SAP Analytics Cloud, and their capabilities into one fully managed SaaS solution for all data and analytics needs.
It seamlessly integrates mission-critical SAP data with third-party sources—without losing business context or requiring constant extraction.
SAP transforms and harmonizes business data within a hyperscaler environment, ensuring high-quality, ready-to-use data across the board.
Prebuilt SAP Business Data Cloud Intelligent Applications deliver instant, AI-powered business insights with minimal setup, accelerating decision-making and innovation.

Ultimately, SAP BDC helps organizations:

Streamline operations with advanced data pipelines
Accelerate innovation through AI and predictive analytics
Improve agility by enabling teams to respond to change quickly
Drive business growth by turning data into a competitive advantage

Happy Learning!

Swati Gawade-Shingade.

Cognizant technology Solutions.

You may also go through below blogs

SAP BDC for Dummies - SAP Community

SAP BDC Key Features - SAP Community

Deep Dive into SAP BDC Data products - SAP Community

CPI Integration with BW/4HANA

2025-08-02T10:00:58.796000+02:00

Introduction

The below blog provides an overview of setting up a simple CPI integration to post data to a SAP BW/4HANA on-premise instance. I have included an explanation of how to achieve this in both postman and SAP Cloud Integration. I have also included references to helpful blogs you can refer to for additional details.

Set up in BW

Create DSO in BW

Ensure 'Write Interface Enabled' attribute is set.

Add fields to DSO

Download URL's shown on DSO

Get Structure	https://server:port/sap/bw4/v1/push/dataStores/da_maze
Get Sample Data	https://server:port /sap/bw4/v1/push/dataStores/da_maze/sampleData{?records,seed}
Send Data	https://server:port /sap/bw4/v1/push/dataStores/da_maze/dataSend{?request,datapid}
Open Request	https://server:port/sap/bw4/v1/push/dataStores/da_maze/requests
Close Request	https://server:port /sap/bw4/v1/push/dataStores/da_maze/requests/{request}/close{?error}

Using DSO in Postman

For Info can query DSO structure

Or see an example json payload

Post data in postman:

Step 1: Fetch CSRF token

Add header for x-csrf-token = fetch, set Authorization to basic Auth

Response header will contain the csrf token

Step 2: Send Data to BW

Add header x-csrf-token and set value returned by call in Step 1 (found in the response header)

Set body to message to post to BW (xml in this example)

Response back

Example JSON POST

Data Post example in CPI

The process below mirrors the process done previously in postman to post data to BW

Against the Integration flow set HTTP session

Start Timer - Schedule set to Run Once
Set Csrf token header

3. Make http call to get csrf token returned (note that in this example an on-premise BW is being called so virtual host/port have been set in cloud connector)

Make sure Headers are both passed to the call and returned

4. Handle Cookies - The initial csrf call returns an header called 'set-cookie', unfortunately the call to post the data requires an header called 'cookie'. The groovy script converts the format and name. More details can be found in https://help.sap.com/docs/SUPPORT_CONTENT/sci/3361897820.html?locale=en-US

import com.sap.gateway.ip.core.customdev.util.Message;

def Message processData(Message message) {

def headers = message.getHeaders();

def cookies = headers.get("set-cookie");

message.setHeader("cookie", String.join("; ", cookies));

return message;

}

5. Set content type and payload of data post

6. HTTP call to post data to BW

Referenced Blogs:

Integrating with BW

From <https://community.sap.com/t5/technology-blog-posts-by-sap/sap-bw-4hana-write-interface-enabled-adso-connected-to-a-3rd-party-tool/ba-p/13482277>

Example CPI to BW

https://community.sap.com/t5/technology-blog-posts-by-sap/sap-cloud-platform-integration-cpi-to-push-data-into-sap-bw-4hana/ba-p/13418310

Issues with x-csrf not working see below:

https://community.sap.com/t5/technology-blog-posts-by-members/x-csrf-token-with-on-premises-sap-system-using-http-receiver-adapter/ba-p/13533518

https://help.sap.com/docs/SUPPORT_CONTENT/sci/3361897820.html?locale=en-US

SAP Business Data Cloud Series – Part 3: Customer-Managed or Custom Data Products

2025-09-10T04:27:11.039000+02:00

Introduction:

In Part 1(SAP Business Data Cloud Series – Part 1: Introduction to Data Products) of this blog series, we explored the fundamentals of Data Products in SAP Business Data Cloud (BDC). In Part 2(SAP Business Data Cloud Series – Part 2: Extend SAP S/4HANA Managed Data Products) we explored on how to extend SAP S/4HANA Data Products. Now, in Part 3, we dive into the practical aspect of creating custom data products for the source SAP S/4HANA Cloud Private Edition and Share it with SAP databricks.

In this article, we’ll explore a common scenario where a customer has a custom CDS entity in SAP S/4HANA and wants to harmonize its data with SAP-managed data products. We’ll demonstrate how to create a custom data product based on that custom CDS entity, for example, ZCDS_CAMPAIGN and how to delta-share with SAP databricks.

High-level Workflow for the SAP S/4HANA, Customer Managed Data Product:

Steps to create a SAP S/4HANA Customer Managed Data Product.

1. Identify, create, or extend a CDS entity: To build a customer-managed data product in an SAP S/4HANA system, the recommended approach is to leverage CDS views/entities. In this example, we’ll create a custom CDS entity as shown below.

Note: As a best practice, customers should leverage SAP-released CDS views first, extend them where needed, and only create custom CDS views when business requirements demand it. This is fully permissible under the clean core paradigm, as business requirements ultimately take priority.

@ObjectModel.usageType.dataClass: #TRANSACTIONAL
@ObjectModel.usageType.serviceQuality: #A
@ObjectModel.usageType.sizeCategory: #XL
@ObjectModel.representativeKey: 'CampaignID'
@ObjectModel.modelingPattern:         #ANALYTICAL_DIMENSION
@ObjectModel.supportedCapabilities: [ #ANALYTICAL_DIMENSION,
                                      #CDS_MODELING_DATA_SOURCE,
                                      #CDS_MODELING_ASSOCIATION_TARGET,
                                      #SQL_DATA_SOURCE,
                                      #EXTRACTION_DATA_SOURCE ]

@ObjectModel.sapObjectNodeType.name: 'CampaignID'
@EndUserText.label: 'CDS View for Campaigning Data'
@Analytics.dataCategory: #DIMENSION
@Analytics.internalName: #LOCAL
@Analytics: {
    dataExtraction: {
        enabled: true,
        delta.changeDataCapture: {
            mapping:[
                {
                    table: 'zcampaign', role: #MAIN,
                    viewElement: ['CampaignID'],
                    tableElement: ['campaign_id']
                }
            ]
        }
    }
 }

@VDM.viewType: #BASIC
@Metadata.allowExtensions: true
@Metadata.ignorePropagatedAnnotations: true

define view entity ZCDS_campaign as select from zcampaign
{
 @EndUserText.label: 'Campaign_ID'
    key zcampaign.campaign_id as CampaignId,
    @EndUserText.label: 'Campaign_Name'
    zcampaign.campaign_name as CampaignName,
     @EndUserText.label: 'Channel'
    zcampaign.channel as Channel,
    zcampaign.type as Type,
    zcampaign.start_date as StartDate,
    zcampaign.end_date as EndDate,
    zcampaign.status as Status,
     @Semantics.amount.currencyCode: 'BudgetCurrency'
    zcampaign.budget as Budget,
    zcampaign.budget_currency as BudgetCurrency,
     @Semantics.amount.currencyCode: 'ActualSpendCurrency'
    zcampaign.actual_spend as ActualSpend,
    zcampaign.actual_spend_currency as ActualSpendCurrency,
    zcampaign.created_by as CreatedBy,
    zcampaign.created_on as CreatedOn
    
}

2. SAP S/4HANA Private Cloud or On-Premise Edition requires a Cloud Connector: Configure the Cloud Connector to enable communication between your on-premise/private cloud system and SAP Datasphere (public cloud). This setup is a prerequisite for creating an SAP S/4HANA or ABAP connection in SAP Datasphere for using the replication flow feature.

SAP Datasphere Integration with SAP S/4HANA: SAP Cloud Connector Setup Guide

3. Create a Datasphere Space of Type HANA Data Lake Files: An administrator can create a space backed by SAP HANA Data Lake Files in the object store. File spaces are designed for cost-efficient staging, loading, and preparing large volumes of data.

For detailed instructions, refer to the help guide: Create a File Space in the Object Store.

Additional configuration is required while configuring the SAP Datasphere tenant. e.g. Memory must be 128GB or more. Check via SAP BDC Estimator.

If you have configured correctly then you should also see the same under the SAP Datasphere, Tenant configuration. Please note this view is only available to the SAP Datasphere system owner.

SAP Datasphere object store: Storage type will be SAP HANA Data Lake Files. In our scenario we have created a space with a name Workshop: OBJECT STORE.

4. Create a SAP S/4HANA Connection in the SAP Datasphere Object Store Space, Workshop: OBJECT STORE :

4.1 Create a new connection or use the existing connection of type SAP S/4HANA on-premise or ABAP:

4.2 Fill in the connection configuration details as show below and important step is select the cloud connector which was setup and configured in the step 2.

4.3 Provide the connection name and description:

4.4 Validate and test the connection making sure replication flows are enabled:

You can also use or create the SAP ABAP connection type for this use case.

5. Create a Replication Flow to Load Data from CDS Entity into SAP Datasphere Object Store (HDLF):
Set up a replication flow with the source system SAP_S4H_RI4 and CDS entity ZCDS_CAMPAIGN. Define the target as a Datasphere local table ZCDS_CAMPAIGN_BRONZE. This table, serving as the Bronze layer, will store source records and structures in their original form.

5.1 Create a new replication flow

5.2 Select the Source SAP_S4H_RI4 and Container (Source Objects) ZCDS_CAMPAIGN

5.3 Select the target as connection as a SAP Datasphere

5.4 Provide the target object local table name ZCDS_CAMPAIGN_BRONZE and Deploy the replication flow.

5.5 Execute the replication flow and check the run details.

5.6 Perform the merge table activity:

5.7 Post merge table activity, data will be available to preview and Test it.

6. Bronze to Silver layer medallion transformation using a Transformation Flow: In many cases, data from the Bronze layer needs to be refined into a Silver layer through transformations such as splitting, merging, adding/removing columns, joins, or unions.

In our scenario, we will split the values in the Channel column into two columns Channel, Allocated Percentage (multiple rows) and apply necessary calculations.

6.1 Create a new Transformation Flow

6.2 Define the transformation steps:

Source table:HDLFT_CAMPAIGN_BRONZE and Target table: HDLFT_CAMPAIGN_SILVER . Python script operator for performing the transformation logic.

def transform(data):
    """
    This function body should contain all the desired transformations on incoming data of Pandas DataFrame.
    Permitted builtin functions as well as permitted NumPy and Pandas objects and functions are available inside this function.
    Permitted NumPy and Pandas objects and functions can be used with aliases 'np' and 'pd' respectively.
    Python standard libraries like 'time', 'datetime', 're', 'random', 'math', 'calendar' and 'dateutil.parser' can be used without any alias.
    This function executes in a sandbox mode. Please refer the documentation for permitted objects and functions.
    Using any restricted functions or objects would cause an internal exception and result in a run failure.
    Any code outside this function body will not be executed and inclusion of such code is discouraged.
    :param data: Pandas DataFrame
    :return: Pandas DataFrame
    """
    #####################################################
    # Provide the function body for data transformation #
    #####################################################
    rows = []

    for _, row in data.iterrows():
        channel_str = row['Channel']

        if pd.isnull(channel_str) or not str(channel_str).strip():
            continue

        entries = str(channel_str).split(';')
        channel_map = {}  # To store channel_name -> summed Decimal %

        for entry in entries:
            entry = entry.strip()
            if not entry:
                continue

            if '(' in entry and '%' in entry:
                channel_name = entry.split('(')[0].strip()
                percent_str = entry.split('(')[1].replace(')', '').replace('%', '').strip()

                try:
                    percent_val = Decimal(percent_str)
                except:
                    percent_val = Decimal('0')

                if channel_name in channel_map:
                    channel_map[channel_name] += percent_val
                else:
                    channel_map[channel_name] = percent_val

        for channel_name, total_percent in channel_map.items():
            new_row = row.copy()
            new_row['Channel'] = channel_name
            new_row['AllocatedPercentage'] = total_percent
            
            if total_percent > 0:
                new_row['ActualSpend'] = (new_row['ActualSpend'] * (total_percent/100) )
            
            rows.append(new_row)

    data = pd.DataFrame(rows)
    return data

6.3 Execute the transformation flow and test the output from the local table HDLFT_CAMPAIGN_SILVER:

Wonderful our silver layer of the data is ready and transformed as per the business requirement. Now let us create the customer managed data product and share with the SAP databricks. You can also share the local table from HANA Data Lake File space to HANA cloud DB space and build the models on top of it, e.g. Building a report that provides access to 5 years of worth where most recent 2 years are persisted on the storage type in-memory/disk while rest 3 years are persisted on the storage type file and union model is build to combine this data.

7. Creating Custom Delta Share Data Products: Create a Formations Profile with Data Product visibility option as Formations.

8. Context is automatically created.

9. After creating your Unified Customer Landscape Formations profile, you can proceed to create a Delta Share data product:

10. List the Custom Data Product, so that It will be discoverable in the SAP BDC Catalog & Marketplace:

11. Search and Discover the Data Product "Sales Campaign Gold Data" in SAP BDC Catalog & Marketplace:

12. Share the Data Product "Sales Campaign Gold Data" with supported BDC target systems in our scenario it is SAP databricks: We are sharing the data product with SAP databricks workspace WS_IT.

Note: SAP databricks is part of our SAP BDC formation, hence it is available under the target system options.

13. Validate the sharing is enabled and correct target system:

14. Validate the Delta-Shared Sales Campaign Gold Data product in SAP Databricks by checking the WS_IT workspace with verifying its presence and data preview in the Unity Catalog.

Summary:

In this part of the SAP Business Data Cloud (BDC) series focusing on the data products, we explored how to build a custom data product in SAP S/4HANA Cloud Private Edition using a custom CDS entity (e.g., ZCDS_CAMPAIGN). We walked through setting up prerequisites like the Cloud Connector, creating a Datasphere file space, and configuring connections. Using the bronze–silver transformation approach, we replicated and refined campaign data for harmonization. Finally, we created and published a custom Delta Share data product, making it discoverable in the BDC Catalog and consumable in SAP Databricks for advanced analytics and ML scenarios.

🌟 Highlights: Enterprise Architects Guide on SAP BW Modernization 🌟

2025-09-30T16:49:38.710000+02:00

We wrapped up an in-depth session – expertly introduced by Gaurish – on “Architecting your SAP Business Data Cloud (BDC) Journey from Data to Intelligence." Sandy, Justin, and Jason shared practical viewpoints for anyone charting a course from legacy SAP BW to the world of SAP’s Business Data Cloud.

🔍 Why Modernize SAP BW?
Justin emphasized how SAP BW has shaped enterprise analytics for 25+ years. However, remaining on legacy systems increases risks and costs, while stifling innovation. The move to modern, multi-cloud data platforms is essential to sustain business continuity and stay competitive.

🚀 Unveiling the SAP Business Data Cloud Advantage
Modernizing to BDC offers a unified and scalable SaaS platform that blends SAP and non-SAP data, infuses AI and machine learning, and boosts analytics and data governance. It preserves business relationships and metadata, providing more business context than ever possible with classic BW.

🛣️ Strategic Pathways & Migration Options
Successful modernization starts with a BW landscape assessment. SAP supports this with a free assessment and discovery workshop to catalogue your environment and match the right transition pathway—whether it’s greenfield, system conversion, or embedded scenarios. Focus is on minimizing business disruption and maximizing long-term agility.

🛠️ The Data Product Generator in Action
Sandy’s live demo showed how the Data Product Generator lets organizations extract BW InfoProvider data into SAP Datasphere’s object store - supporting cost-effective storage and simplified creation of data products ready for analytics and AI in Databricks, Datashare, and more.

🔗 Smooth BW-BDC Transitions & Reference Patterns
The ability to push data from BW into BDC via dedicated inbound spaces, define granular subscriptions, and link to intelligent applications in SAC allows gradual, disruption-minimized modernization. Sandy outlined technical steps, naming conventions, and how semantic information and associations enhance downstream analytics.

🏛️ Enterprise Architecture Viewpoints
Jason gave a holistic lens on this transformation, urging enterprise architects to align their strategy on security, governance, business stakeholder impact, and organizational change management. Modernization isn’t just about technology—it’s about culture, skills, and sustainable strategic alignment.

🎉 Customer Success, Services & What’s Next
SAP’s BDC Discovery Workshop and free readiness assessment were spotlighted—helping organizations begin their modernization journey with confidence. Participants gained clarity on prerequisites for custom data products, and how future capabilities like the Data Product Studio will shape self-service data management.

SAP Migration Assessment: https://www.sap.com/products/data-cloud/sap-migration-assessment.html

🙌Huge thanks to everyone who joined and asked great questions! Special thanks to Sandy for the impromptu deep dive and hands-on demo.

👉Stay tuned for the next session: “Fast Track to SAP Business Data Cloud” featuring fresh perspectives from the Data & Analytics community.

Registration Link: https://events.sap.com/eaa-bdc-apac/en_us/home.html#accordion-5d79451476-item-7fc89659c4

@Gaurish-Dessai @SandyTran @Justin-Zhang

How to Identify Selections Used in RKFs in Rows/Columns of BW/BEx Queries

2025-10-09T12:28:22.271000+02:00

In continuation of my previous blog (Section 5 of All about Bex Query elements in SAP BW/BW4HANA - SAP Community), this post focuses on example involving Restricted Key Figures (RKFs) in SAP BW/BEx queries.

In this blog, I explain the best way to extract or identify the selection criteria applied in RKFs that are used in the rows or columns of a BW/BEx query.

When a query contains only a few rows or columns (e.g., 5–10), it's relatively easy to manually check the selections used in each RKF. However, in more complex reports such as Balance Sheet or Income Statement reports with over 50 rows manually checking each row or column becomes time consuming and inefficient.

To overcome this challenge, we can leverage backend SAP BW tables to extract the relevant details and analyze them in Excel. The key tables involved in this process are:

RSRREPDIR – Query directory
RSZELTXREF – Element cross-reference
RSZRANGE – Selection ranges
RSZELTDIR – Element directory

By correlating these tables, we can efficiently retrieve the selection criteria used in RKFs that are used in the rows or columns of a BW/BEx query, saving significant manual effort.

Steps to Identify Selections Used in RKFs in Rows and Columns of a BW/BEx Query.

Step 1: In the Table RSZCOMPDIR / RSRREPDIR enter the query technical name in the field COMPID to obtain the COMPUID of the query.Screenshot 1 : Output of RSRREPDIR table

Step 2: In the RSZELTXREF table, enter the COMPUID of the query (from step 1) in the field SELTUID to obtain TELTUID.Screenshot 2 : Output of RSZELTXREF table

Step 3: Again, in the RSZELTXREF table, enter TELTUID (from step 2, where LAYTP = ‘SOB’) in the field SELTUID and execute the table.Screenshot 3: Output of RSZELTXREF table

Step 4: Again, in the RSZELTXREF table, enter TELTUID (from step 3, where LAYTP = ‘COL/ROW’) in the field SELTUID and execute the table.Screenshot 4 : Output of RSZELTXREF table

Note : If there are direct selections (i.e., no RKFs) used in the rows/columns of the query, you can skip Step 5 & 6 and proceed directly to Step 7.

Step 5: Again, in the RSZELTXREF table, enter TELTUID (from step 4) in the field SELTUID and execute the table.Screenshot 5 : Output of RSZELTXREF table

Repeat Step 5 until the RSZELTXREF table returns zero entries.

Step 6: Collect all TELTUID values from the previous steps into an Excel sheet and remove any duplicates.Screenshot 6 : List of all TELTUIDs from all steps

Step 7: Go to the RSZRANGE table and enter the TELTUID values (from Excel) into the SELTUID field. Execute the table to retrieve the selection details used in the rows and columns.Screenshot 7 : Selection details

Step 8: Open the RSZELTDIR table and enter the same TELTUID values (from Excel) into the SELTUID field. Execute the table to get the technical names and descriptions of the elements.Screenshot 8: Technical names and descriptions of the elements

Step 9: Download the outputs from Step 7 and Step 8 into Excel. Use the VLOOKUP formula to match and enrich the selection data from Step 7 with the descriptions from Step 8 Screenshot 9 : Final output with all required details

Conclusion : In complex SAP BW/BEx queries, especially those used in financial reports with numerous rows and columns, manually identifying selection criteria in Restricted Key Figures (RKFs) is inefficient. By leveraging backend BW tables such as RSRREPDIR, RSZELTXREF, RSZRANGE, and RSZELTDIR, users/Developers can systematically trace and extract RKF selections. This approach enables efficient analysis in Excel, significantly reducing manual effort and improving transparency in query design.

Happy Learning 😊

Building Bridges Between SAP and Databricks: A Dream Team for Your Data and AI-Powered Analytics

2025-10-28T13:25:22.036000+01:00

The Interplay of SAP & Databricks: Why Now?

The combination of SAP and Databricks is more than just a technical integration; it is a strategic course-setting. It brings together the best of two worlds:

SAP as a Stable Foundation: Your SAP systems contain the most important business data—from financial key figures to master data. This data is not only comprehensive but also semantic and contextual, making it an ideal basis for training AI models.
Databricks as an Innovation Engine: Databricks offers a scalable platform for Data, Analytics, and AI. It is a powerful engine for machine learning and complex analyses, enabling companies to gain valuable insights from large amounts of data.

This Dream Team transforms corporate management. Instead of merely answering questions like "What happened?", Business AI enables a look into the future: "Why did it happen?" and, most importantly, "What will happen and what should we do?".

Figure 1: Interplay of SAP & Databricks

The Benefits of Integration at a Glance

The partnership between SAP and Databricks offers tangible benefits that are evident at the strategic, technical, and operational levels.

Strategic Advantages

The integration ensures open data management and analytics for SAP and non-SAP data. Complete alignment with the SAP Business Data Cloud with strong governance creates a future-proof architecture. The simplified pricing model in general Capacity Units also makes the start easier to plan.

Technical Advantages

The platform is designed to allow extended use via interfaces and can scale with growing demands and data volumes. The seamless integration of the SAP Business Warehouse and SAP S/4HANA with data products enables an end-to-end process. An important difference when deciding for or against an SAP Databricks: The SAP Databricks is fully managed by SAP. This means it is technically operational immediately.

Operational Advantages

Companies benefit from a Hyperscaler infrastructure, which ensures resilience and a reduction in Total Cost of Ownership (TCO). Technical operation is supported by Managed Services from SAP, which reduces complexity in day-to-day business and allows for the installation of upgrades on demand.

How the Dream Team Works in Practice

Databricks offers a number of key elements to enable integration and analysis:

Unity Catalog: The Unity Catalog serves as a central landing zone for governance and data products. Metadata is managed here and the data is stored in Delta Tables, ensuring a consistent view of your information and secure access.

Figure 2: Databricks Unity Catalog: The landing zone for governance and data products.

Databricks Workspace: Modeling and development take place in the Databricks Workspace. Users work here with interactive notebooks, which offer an encapsulated programming interface for agile and flexible work. SQL, Python, R, and Scala are supported as languages.

Figure 3: Databricks Workspace: Modeling takes place in Databricks within the Workspace, using "Notebooks" among other tools.

Databricks Machine Learning: The integration of MLflow enables the training, versioning, and deployment of models. The clear management of training runs and the linking of datasets significantly simplifies the establishment of professional AI in the company. Important to know: The operation of Machine Learning models should strategically take place in SAP AI Core, although Databricks also supports this functionality depending on the use case.

Figure 4: Databricks Machine Learning. Model training (experiments), model versioning, or the deployment of models on one platform.

Conclusion: From Dataset to Smart Decision

The combination of SAP and Databricks elevates data analysis to a new level. Your financial key figures and master data serve as a reliable source for intelligent analyses. The integration with Databricks makes it possible to automatically recognize patterns and correlations from this data. The platform's flexibility and scalability allow complex AI models to be applied and the resulting cluster information seamlessly fed back into your SAP world to enable users to make well-founded decisions. The deep and exclusive technical integration of both worlds guarantees a secure and fast exchange of data products.

Key Takeaways for Your Company

Data and AI are moving closer together: The separation between data storage (SAP) and data analysis (Databricks) is a thing of the past. The seamless integration allows your most valuable business data to be used directly for modern AI applications. This creates a unified information base and eliminates fragmented data silos.
High Potential through Synergies: The combination of SAP’s standardized data storage and proven processes with Databricks’ innovative AI technology opens up completely new possibilities. You can not only see what happened but also why it happened and what will happen next. This empowers you to act proactively and identify risks early on.
Professional AI Establishment: The Databricks platform offers a mature environment for professionally establishing AI applications in the company. Thanks to functions like Unity Catalog for data governance and Databricks Machine Learning for model training, you can ensure that your AI initiatives are scalable, secure, and sustainable.

How You Can Get Started Now: Our Practical Advice

Many companies hesitate to take the first step because the topic seems complex. However, getting started doesn't have to be overwhelming. We recommend starting with a Proof-of-Concept (PoC).

Define a Clear Use Case: Choose an area in your company where data analysis can bring real added value. This could be optimizing inventory management, predicting customer behavior, or automating financial forecasts.
Utilize Your Existing Potential: A PoC helps you assess how you can tap into your unused data potential. This provides concrete results and allows you to prove the business case for a broader implementation.
Start Small to Grow Big: Begin with a manageable project to achieve quick successes and build confidence in the new technology. The scalability of the platform allows you to easily add more use cases later.

The partnership between SAP and Databricks is not a futuristic concept but a practice-oriented solution that helps you make data-driven decisions and future-proof your company. The time to awaken your SAP data from its slumber is now.

Now it’s your turn: What experiences have you already had with using SAP data for intelligent analyses? What challenges do you see on the path to Business AI? We look forward to your perspectives and to shaping the future of data analysis together.

Evolution of Data and Analytics with SAP Business Data Cloud

2025-11-06T08:37:22.657000+01:00

Introduction to Business Data Cloud:

SAP Business Data Cloud was introduced on February 13 2025 as Software-as-a-Service (SaaS) solution fully managed by SAP. SAP Business Data Cloud is a data & analytics platform that harmonizes all data from SAP and non-SAP sources into a unified semantic layer of trusted data that governs, connects and share data securely across systems or cloud. By integrating powerful functionality of SAP Datasphere, SAP Analytics Cloud, and SAP Databricks and SAP Business Warehouse. It empowers businesses to break data silos to power advanced AI and analytics.

Why was Business data cloud introduced?

To get easier access to SAP data without the need for complex data preparation steps such as extraction, building semantics, transformation and loading data for analytics.
To get access to all SAP data from all Line of Business (LoB) applications, such as SAP S/4HANA, SAP SuccessFactors and SAP Ariba without the need of 3rd party connector & tool.
To get a unified business view of the data regardless of which SAP application it originated from without making harmonization difficult and holds its original business context without any change.
To accelerate AI with trusted and secure data that they can use to build reliable AI applications to accelerate innovation and insights with AI.
To get faster access to SAP data insights by removing data preparation and dashboard building steps.
To get a Simplified Landscape by reducing multiple tools, silos and complex tasks of manual data preparation, development and analytics.

Key Features & Capabilities of Business Data Cloud:

SAP Business Data Cloud Key Innovation of out-of-the-box components

Intelligent Applications: Intelligent Applications are predefined, SAP-managed dashboards for analytics based on underlying Data Products and models.
Data Products: Create and share governed, reusable data products that deliver consistent, high-quality business information across teams and systems.
BDC Cockpit: Centrally manage your data products, monitor usage, and enforce governance policies, all from one intuitive interface.

SAP Business Data Cloud Integrated Software components:

SAP Datasphere: to provide the data integration and modelling.
SAP Analytics Cloud: to provide the analysis and planning.
SAP Databricks: to provide AI and machine learning enhancements.
SAP BW/BW4HANA: can be used as a data source for datasphere & databricks.

SAP Business Data Cloud is built on SAP Business Technology Platform:

Unified Customer Landscape used to connect the SAP Business Data Cloud components.
SAP HANA Cloud provides the data storage layer.
SAP Security and Compliance to manage access and permissions and governs regulatory compliance.
SAP Development & Integration to provide developer tools for modelling & data Integration
SAP AI & Analytics to provide advanced analytics and AI powered insights.

SAP Business Data Cloud Architecture:

Source System layer: It harmonizes all data from SAP and non-SAP sources, into a unified semantic layer of trusted data, to power advanced analytics and to build AI applications.
Foundation Service Layer: This layer replicates and harmonizes data from the source systems to produce curated, governed Data Products that retain their original business context. Data products are grouped by Data Packages to make it easy to discover them and to activate them. This data is stored in a hyper scaler environment using SAP HANA Cloud and Data Lake files.
Business Data Fabric Layer: It combines the strengths of SAP Datasphere, SAP Analytics Cloud (SAC), and SAP Business Warehouse (BW) capabilities, enhanced by the Databricks platform to unify an organization with SAP and Non – SAP and third-party data into a single, trusted foundation model.
SAP Datasphere is the technological foundation for the business data fabric within BDC. It integrates, transforms, and enriches data from SAP and non-SAP sources into powerful semantic models. Data can be replicated into Datasphere for faster performance or accessed virtually from its source, allowing for flexible management of a hybrid data landscape.
SAP Databricks is an Advanced AI and machine learning technology. It provides a pro-code environment for data engineers and AI developers to build, train, and deploy custom AI and ML models using the rich, semantically aware data from SAP applications.
SAP Business Warehouse (BW) or BW/4HANA: For customers with existing on-premises SAP Business Warehouse (BW) or BW/4HANA systems, this component provides a modernization path within the Business Data Fabric. A Data Product Generator can be used to convert BW Info Provider data into cloud-ready data products, which can then be consumed by Datasphere for analytics or by Databricks for AI/ML.
SAP Business Data Cockpit: SAP Business Data Cloud cockpit allows you to browse and find pre delivered Intelligent Applications and data products, install Intelligent Applications, and share data products with SAP Datasphere & Databricks to enable analytics & enrich with AI and machine learning capabilities.
Intelligent Application Layer: It’s a unified semantic layer of trusted data, to power advanced AI & Analytics.
SAP Analytical Cloud: Using SAP Analytics Cloud, business users can run ad-hoc analysis, explore the provided data with AI-driven chat capabilities, or act on their insights with AI-driven suggestions, bridging the gap between analytics and their end-to-end business processes.
Intelligent Application: SAP Business Data Cloud Intelligent Applications are used to provide the required dashboard in out-of-the-box reporting scenarios with its advanced visualization and planning functions
Joule: Joule uses natural language processing to interact, access insights, and perform tasks across SAP and third-party applications. It uses "agents" and "skills" to automate multi-step workflows and provide contextual assistance.

How SAP Business Data Cloud work as one domain model:

Scenario 1: Out-of-the-Box model with Datasphere

Step 1: The first step is to identify the right intelligent application for your business scenario, In SAP Business Data Cloud cockpit search for available intelligent application and install the one that meets your requirement.

Step 2: When intelligent application installation is initiated the relevant business data that has already been bundled into a package in your business application is accessed and replicated to the Foundation Services of SAP Business Data Cloud.

Step 3: Inside the Foundation Services, the replicated business data is harmonized with other data packages from different business applications such as SAP SuccessFactors the data is transformed and enriched to become a data product. The data is now ready to be used as the basis for analysis.

Step 4: In SAP Datasphere all artifacts necessary for the analysis are now automatically generated on top of the Data Product.

Step 5: Visual representations of the insights are automatically generated and made available in the intelligent application dashboard.

Scenario 2: AI and machine learning enhancement by Databricks

Step 4: In SAP Datasphere all artifacts necessary for the analysis are now automatically generated on top of the Data Product.

Step 5: Visual representations of the insights are automatically generated and made available in the intelligent application dashboard.

Step 6: Integration of SAP Databricks

It is possible to extend the results shown in the dashboard with machine learning and AI based Insights, to do so use the SAP business data cockpit to share data product with databricks,

In SAP Databricks AI and Machine learning techniques are used to generate the desired result, this results then shared back to the data model and extend your dashboard with AI and Machine learning insights.

Scenario 2: : Integration of SAP BW & SAP Analytical Cloud

Step 1: The first step is to identify the right intelligent application for your business scenario, In SAP BDC cockpit search for available intelligent application and install the one that meets your requirement.

Step 4: In SAP Datasphere all artifacts necessary for the analysis are now automatically generated on top of the Data Product.

Step 5: This is where the integration of your third-party data comes into play. The advanced integration and data modelling capabilities of SAP Datasphere allow you to integrate your third-party data into the out-of-the-box data model.

Step 6: Integration of SAP BW

It is also possible to integrate your existing objects from SAP BW/4HANA into SAP Business Data Cloud. With a dedicated data provisioning tool, you can onboard your SAP BW objects into SAP Datasphere and combine them with the existing data model.

Step 7: Integration of SAP Analytical Cloud

SAP Business Data Cloud provides a wide range of consumption options on top of your data model. Use the AI-based Just Ask feature in SAP Analytics Cloud. The power of its natural language processing allows you to request information from your data model simply by typing a question about your data. Answers are instantly displayed in the most appropriate format.

Role of Source system & Data product in BDC:

Role of Datasphere in BDC:

Role of Databricks in BDC:

Role of BW in BDC:

Role of SAC in BDC:

Role of Intelligent Application Dashboard & Joule in BDC:

Use Case of Business Data Cloud:

SAP Business Data Cloud can handle many use-cases including:

Data Integration & Modelling
Data Governance and Compliance
Development of AI and machine learning models
Data Warehousing
Planning and BI
Development of intelligent applications to support all business processes.
End-to-end data lifecycle management by SAP

SAP Business Data Cloud reaches all personas of the organization.

Conclusion:

Data from all SAP applications is combined and made available to the businesses under a single domain model. With SAP Business Data Cloud, SAP has reached the next level of data and analytics evolution to tackle challenges and enables businesses to seamlessly integrate, harmonize, and analyse data from multiple sources, transforming raw data into valuable insights with advanced AI and analytics.

By adopting the latest 2025 features, organizations can accelerate analytics, improve decision-making, and prepare for AI-driven innovation.

Reference:

Learning Journey: https://learning.sap.com/learning-journeys/exploring-sap-business-data-cloud
Live Session : https://learning.sap.com/live-sessions/overview-of-sap-business-data-cloud
SAP Help Document : https://help.sap.com/docs/business-data-cloud
GenAI Assistance : Assistance in drafting the structure of blog.

Handling Record Count Mismatches After HANA Tenant Copy During S/4HANA On-Premise to RISE Migration

2025-11-17T06:25:35.927000+01:00

As part of a system move, We performed a HANA tenant copy from our on-premise S/4HANA system to the RISE environment. After completing the tenant copy, we compared the total record count of the SAPABAP1 schema using:

SELECT SUM(RECORD_COUNT) FROM M_TABLES WHERE SCHEMA_NAME = 'SAPABAP1';

Source Record count:

Target Record count:

A small difference appeared between the source and the target system.
To validate the result, We first checked whether any column-store tables were unloaded using:

SELECT SCHEMA_NAME, TABLE_NAME FROM M_CS_TABLES WHERE LOADED = 'NO';

No unloaded tables were found, so the values from M_TABLES were correct for comparison.

To investigate the difference, I exported and compared the table-level record counts.

The mismatch came from the following tables:

Table Name	Source	Target
/BI0/0K00193590	1	0
/BI0/0K00193626	2	0
/BI0/0K00193632	2	0
/BI0/0K00193575	1	0

All of these objects belong to the /BI0/ namespace.

Information provided by SAP clarifies that these objects are temporary BW tables, as described in SAP Note 2800007.
They are created during BW processing and are not persistent. So we took the confirmation and ignored these tables as they are temporary tables.

Additional related details include:

Hash / union temporary tables (40-character names)
These store intermediate results for hierarchy queries. They are copies of 0BW:BIA:BI0* objects with a retention time. Unneeded tables are removed using BW cleanup tools such as:

Report SAP_DROP_TMPTABLES
Function module TREX_DBS_DROP_BW_UNION_TABLES
Notes 2838176 and 2852066 describe adjustments and cleanup behaviour.

Temporary tables in the pattern 0BW:BIA:BI0*
These hold temporary hierarchy or F4 help data. They are cleaned automatically or through report RSDDTMPTAB_DELETE.
SAP Note 3316894 describes a case where automatic cleanup may not run as expected.

According to this information, differences in these temporary table counts between systems are normal and depend on BW usage and cleanup cycles.

An important point :- it's necessary to exercise maximum caution before dropping these tables. Consultation with a BW consultant is advised.

Conclusion:

The record count mismatch observed after the HANA tenant copy was limited to BW temporary tables described in SAP Note 2800007. These tables are not persistent and may exist or be cleaned up at different times in different systems. Because of this, small differences in their record counts are expected and do not indicate any issue with the tenant copy. The overall tenant copy can be considered consistent and successfully completed.

XPRAS Error During MAIN_NEWBAS/XPRAS_AIMMRG in S/4HANA Conversion Execution Phase

2025-11-21T16:55:01.689000+01:00

During the recent Oracle → HANA system conversion to S/4HANA 2023, we encountered an error in the Execution Phase where SUM stopped with an error at the step MAIN_NEWBAS/XPRAS_AIMMRG.

Overview

During the SUM execution, the process stopped in MAIN_NEWBAS/XPRAS_AIMMRG due to BW-related inconsistencies. The phase could not continue because certain BW InfoObjects were not fully activated before downtime.

Analysis

While reviewing the error logs (XPRASUPG_NEW.ELG and related BW activation logs), we observed multiple failures related to InfoObject activation.
The XPRAS engine failed to merge certain BW objects because the BW content was not in an active state before SUM was started.
We validated client settings, checked multiple profiles, reviewed shadow logs, and compared BW content activation status before correlating this with the root cause.
Only after detailed log review and cross-checking, it became clear that the system required specific BW preparation activities prior to downtime.

How to Identify

These indicators helped confirm the issue early:

XPRAS error in XPRASUPG_NEW.ELG with BW InfoObject activation entries.
Multiple failed entries referring to missing or inactive InfoObjects.
BW task list not executed before downtime (SAP_BW_SETUP_INITIAL_S4HANA).
Running STC01 or RSDG_IOBJ_ACTIVATE manually showed several inactive objects.
SUM repeating the same activation attempts and stopping again.

This combination confirmed that BW content activation was incomplete prior to the conversion.

Resolution

After confirming the root cause, we performed the below steps to fix the issue:

Implemented the required corrections in Client 000 using a non-DDIC user with SAP_ALL.
Activated the missing BW InfoObjects as per SAP Note 3315495.
Ensured the system was locked again and resumed the SUM execution.
SUM continued successfully without further XPRAS errors.

Workaround (for early detection )

To prevent the issue in the next conversion cycles (QA/DR/Production):

Implement SAP Notes 3305016 and 3316148 before executing SUM.
• Before downtime, run task list:
STC01 → SAP_BW_SETUP_INITIAL_S4HANA
Optionally run:
Program RSDG_IOBJ_ACTIVATE to ensure all InfoObjects are active.
Validate BW readiness in Sandbox during rehearsal runs.

These actions ensure the BW layer is fully consistent before SUM execution begins.

Regards,
Shubham Mishra

Modernizing SAP BW with SAP Business Data Cloud

2025-12-12T08:55:44.659000+01:00

Introduction: How to Truly Unlock the Value of Your SAP Data

Many companies across industries struggle with limited usability of their SAP BW and S/4HANA data. Traditional data-warehouse systems are reaching their limits:

Reports and analytics are delivered too slowly for business units that need them for decision-making
Data landscapes are fragmented, making it difficult to combine SAP and non-SAP data
IT teams face high effort to implement new requirements or prepare data for AI/ML scenarios
Business units that rely on self-service analytics are restricted by the limitations of existing systems

The SAP Business Data Cloud addresses these challenges. It combines the stability and depth of your SAP BW data with the flexibility of modern cloud platforms such as SAP Datasphere and SAP Databricks. This gives business units direct access to data while IT retains control over governance and security. As a result, companies can fully leverage their data for intelligent analytics, AI/ML-driven insights, and flexible reporting.

With the SAP Business Data Cloud, a rigid Business Warehouse environment becomes an agile, future-proof data ecosystem that empowers business users to make faster decisions while protecting existing BW investments.

What Are the Benefits of Integrating BW into the SAP Business Data Cloud?

Strategic Benefits

Full integration into the SAP Business Data Cloud with governance and security
Open data management for SAP and non-SAP data
Unified platform for applications and operations from a single provider
Future-proof technology

Technical Benefits

Scalable cloud platform that grows with increasing data volumes and requirements
End-to-end integration of SAP BW & S/4HANA into data products
Support for out-of-the-box and custom scenarios
BDC Connect & Delta Share enable zero-copy data exchange with other platforms
Object Store for flexible provisioning and processing of large data volumes
Metadata analysis via Catalog provides transparency and traceability

Operational Benefits

Resilient hyperscaler infrastructure that reduces TCO
Managed services that relieve the burden on IT teams
Flexible provisioning through interfaces (OData, ODBC/JDBC & BDC Connect) and front ends (SAC, Analysis for Office)

How It Works: Three Phases of BW Modernization

For modernizing your SAP BW landscape into the SAP Business Data Cloud, we recommend a clear, structured three-step approach: “Lift – Shift – Innovate.”
This ensures that existing BW investments are preserved while taking full advantage of a modern, flexible cloud platform.

Figure 1: Lift, Shift, Innovate

Phase 1: Lift – Moving SAP BW into the Cloud

The process begins by migrating your existing SAP BW system to the Private Cloud Edition (PCE). This approach allows you to continue using your familiar BW applications while simultaneously unlocking the first benefits of the SAP Business Data Cloud.

Through the Data Product Generator, your BW InfoProviders are integrated into SAP Datasphere, where they are made available as data products. These can be further refined in dedicated modeling areas called Spaces.

Using this technology, both legacy and new data can be seamlessly combined within a modern SQL-based modeling approach. As a result, business units can immediately leverage this information for reporting, analytics, and initial AI or ML scenarios.

The Object Store additionally enables flexible provisioning of large data volumes, while BW metadata remains fully transparent via the Catalog.

Phase 2: Shift – Immediate Benefits from SAP Business Data Cloud

With your BW system successfully moved to the cloud, phase two begins: immediate access to the SAP Business Data Cloud. Business units can now directly access the data products without waiting for lengthy modernization steps.

Legacy BW data is replicated using the Data Product Generator, making it available in Datasphere for analytics and self-service modeling. Standard (“out-of-the-box”) scenarios can now be extended to better meet individual requirements, while more complex third-party data is handled through custom scenarios.

BDC Connect, combined with Delta Share, provides zero-copy access to external data platforms, enabling flexible data exchange and combination across systems.

Phase 3: Innovate – Full Transition to the SAP Business Data Cloud

In the third phase, your BW environment is fully transitioned into the cloud. Selected data products are gradually either completely migrated to SAP Datasphere or replaced with SAP-managed data products.

This approach allows you to fully leverage the strengths of SAP Business Data Cloud, SAP Datasphere, and SAP Databricks. The platform supports advanced analytics scenarios, including AI/ML models and intelligent applications for reporting and planning.

Traditional BW applications can be phased out step by step without losing existing data or business logic. Business units continue to benefit from self-service capabilities, while IT centrally manages governance and security requirements.

Zero-copy data provisioning via Delta Share ensures that even large data volumes can be efficiently utilized and shared across various systems.

Figure 2: SAP BW on premise vs. SAP Business Data Cloud

Conclusion: Modernizing Your SAP BW Paves the Way for a Flexible Data Future

Modernizing your SAP BW landscape with the SAP Business Data Cloud offers far more than a simple lift into the cloud. This approach enables your organization to efficiently leverage existing data assets, integrate new technologies, and maintain full control over governance, security, and data quality.

The three-phase “Lift–Shift–Innovate” approach transforms SAP BW systems step by step: you preserve your existing investments, gain immediate access to modernized data products, and simultaneously build a flexible platform for future requirements. Business units benefit from self-service models, while IT retains centralized control. With the integration of AI/ML and intelligent applications, a truly data-driven enterprise emerges—one that does not simply collect information but actively uses it to generate value.

The SAP Business Data Cloud provides the foundation for a modern, scalable data architecture: large datasets can be used, analyzed, and distributed flexibly. At the same time, operational effort for maintenance, updates, and interfaces is reduced, making collaboration between IT and business units more efficient and transparent.

Key Takeaways for Your Company

Future-Proof SAP BW Modernization
The three-phase “Lift–Shift–Innovate” approach transitions traditional BW systems step by step into the cloud. This methodology preserves existing investments while unlocking new analytics and reporting capabilities.
Flexible Data Usage with Object Store and Zero Copy
Large data volumes can be centrally used or distributed within the SAP Business Data Cloud—without the need to create data copies. This simplifies the combination of BW, non-SAP, and third-party data and makes AI/ML applications immediately usable.
Self-Service and Customization for Business Units
Intelligent Applications and Spaces allow business units to independently model, adapt, and use data products for their specific reporting needs—without waiting for IT resources.
Integration of AI/ML and Data Science
The platform enables direct use of data for AI and machine-learning scenarios, enabling faster, more precise, and more predictive analytics.
Efficient Governance and Centralized Control
Your IT department retains control over security and access rights, while metadata, data catalogs, and data products remain transparent. This strengthens compliance, traceability, and unified data management across the organization.
Immediate Results with a Gradual Approach
With the structured transition, companies can benefit immediately from modernized data products without having to overhaul their entire BW environment at once. The outcome: reduced risk and higher user adoption.

Now it’s your turn:
What is your strategy for future-proofing and modernizing your SAP BW data? What challenges do you see in moving to the cloud?
Share your experiences, questions, or best practices with us. Your insights help enrich the discussion and open new opportunities to fully unlock the potential of enterprise data.

Filling the gab between BW and Datasphere (a bit): Implementing a few standard variables

2026-01-22T15:38:53.605000+01:00

Introduction

Welcome to the first blog in a series where I'll try my best to close up some of the functionality gabs between the old SAP BW system and SAP Datasphere.
With the end of life for the old SAP BW systems in sight, companies and developers have been diving deep into SAP Datasphere, to build new, exciting solutions, in addition to migrating existing reports.

Personally, I've been involved with several Datasphere implementations now, and one thing I have found myself missing a lot was the standard Exit variables for things like "Current month", "Current year" and so on.

To make my life, and hopefully yours as well, I've recreated a set of the old date / calendar variables.
All the views are bundled in a nice package, which you can download from this GitHub repo.

How to install:

Note: Your Datasphere tenant does not need to be connected to the Content Network for this to work.

One the package is installed, you may, or may not, need to change the source of the view 2VR_CALENDER_WRAPPER, which is the basis of all the other views.
This was simply done to make sure that even if your space does not contain the Time Objects, you only have to remap 1 object.

Go to this GitHub Repo and download the package
Go to your Datasphere tenant and select "Import":
Click Upload and select the package downloaded in step 1.
After the import is complete click the package:
Under "Import Options", map the space:
And click "Import".
(Certain cases): If the view "SAP.TIME.VIEW_DIMENSION_DAY" is not present in the target space open the view 2VR_CALENDER_WRAPPER and replace the source.

How were they implemented:

All the views are implemented as SQL views, and only return a single column, depending on the kind of view, rather than an interval, which some SAP BW variables might give. The reason for that is explained in the example below.

All views have an input parameter, IP_OFFSET, which takes an integer, and will offset the result by one "unit" of time.
So the CALYEAR views will offset one year at a time, the month views will offset one month at the time, and so on.

Example: Analytical Models

In Datasphere, an Analytical Model is the final (kind of, that's not important now) step in the data modelling process.
In your analytical model, you can define different kind of variables, that allows you to derive a value from a view, or a dynamic default.
Note: Deriving select options and intervals are not supported.

In the above example, the user will be prompted to fill in an interval, but will only derive the first value:

If you want an interval, you'll need "Multiple single values".

In the above example, we've provided a view that returns three values, which will act as an interval.
Note: We have also provided the value -1 for the offset.

Which means all the values, 202601, 202512, 202511, and 202510 is offset by -1:

Implemented Variables

I've created variables for the following date objects:

0CALDAY: Date (YYYYMMDD)
0CALMONTH: Cal. Year / Month (YYYYMM)
0CALQUARTER: Cal. Year / Quarter (YYYYQ)
0CALWEEK: Cal. Year / Week (YYYYWW)
0CALYEAR: Calendar Year (YYYY)

Because - well, because those were the ones that had been giving me headaches.

0CALDAY: Calendar Day

View ID	SAP BW Variable ID	Description
2VR_0DATE	0DATE	Current Calendar Day
2VR_0CEPO_CDPDCY	0CEPO_CDPDCY	Last Day
2VR_0CEIO_CDL7CDCY	0CEIO_CDL7CDCY	Last 7 Days
2VR_0CEIO_CDL14CDCY	0CEIO_CDL14CDCY	Last 14 Days
2VR_0CXIO_CDCMCY	0CXIO_CDCMCY	All days in current Month
2VR_0CXIO_CDCQCY	0CXIO_CDCQCY	All days in current quarter
2VR_0CXIM_CDFYCY	0CXIM_CDFYCY	All days in current year
2VR_0CXIM_CDFYPY	0CXIM_CDFYPY	All days in last year

0CALMONTH: Calendar Year / Month

View ID	SAP BW Variable ID	Description
2VR_0CXPO_CMPMPY	0CXPO_CMPMPY	Last Cal. Year / Month previous year
2VR_0CXPO_CMCMPY	0CXPO_CMCMPY	Current Cal. Year / Month previous year
2VR_0CXIO_CMPQPY	0CXIO_CMPQPY	Last Quarter Previous Year
2VR_0CXIO_CMPQCY	0CXIO_CMPQCY	Last Quarter
2VR_0CXIO_CML12PMCY	0CXIO_CML12PMCY	Last 12 Cal. Year / Months excluding Current
2VR_0CXIO_CML12CMCY	0CXIO_CML12CMCY	Last 12 Cal. Year / Months Including Current
2VR_0CXIO_CMCQPY	0CXIO_CMCQPY	Current Quarter Previous Year
2VR_0CXIO_CMCQCY	0CXIO_CMCQCY	Current Quarter
2VR_0CMONTH	0CMONTH	Current Cal. Year / Month
2VR_0CEPO_CMPMCY	0CEPO_CMPMCY	Last Cal. Year / Month
2VR_0CEIO_CML6CMCY	0CEIO_CML6CMCY	Last 6 Cal. Year / Months Including Current
2VR_0CEIO_CML3CMCY	0CEIO_CML3CMCY	Last 3 Cal. Year / Months Including Current

0CALQUARTER:

View ID	SAP BW Variable ID	Description
2VR_0CXPO_CQQ1CY	0CXPO_CQQ1CY	First Quarter of Current Year
2VR_0CXPO_CQCQPY	0CXPO_CQCQPY	Current Quarter of Previous Year
2VR_0CQUART	0CQUART	Current Quarter

0CALWEEK:

View ID	SAP BW Variable ID	Description
2VR_0CWEEK	0CWEEK	Current calendar week

0CALYEAR:

View ID	SAP BW Variable ID	Description
2VR_0PYEAR	0PYEAR	Last calendar year
2VR_0CYEAR	0CYEAR	Current calendar year

BW Modernisation with the SAP BW Data Product Generator

2026-02-25T11:58:10.665000+01:00

The DataProduct Generator for SAP Business Data Cloud in SAP BW/4HANA Administration Cockpit

With the "SAP BW/4HANA DataProduct Generator for SAP BDC" a functionality is availabe as part of the BW/4HANA Administration Cockpit to expose existing SAP BW/4HANA artifacts ( i.e. Advanced DataStore Objects, CompositeProviders and Queries as an InfoProvider) as local tables to the Object Store. For SAP BW 7.5 there is a SAP GUI based UI available. In a second step the Data Sharing Cockpit of Datasphere can be used to create DataProducts out of such local tables.

1) Activities in the Data Provisioning Cockpit:

Scenario: The underlying Scenario of this chapter is to create a DataProduct out of an Advanced DataStore Object from a SAP BW/4HANA system in the private Cloud which containes additional CashFlow data. This data should be made available as a DataProduct to BDC to be merged with the existing Working Capital data from the exercises before.

Update March 2026: Since the availability of SAP BW/4HANA Modeling Tools in Eclipse 1.27 there is an additional way to move a BW/4HANA InfoProvider to the Object Store of SAP Datasphere (as a basis for the Data Product generation). As a result, a subscription is generated. A data subscription is a new BW object type that allows you to extract data from ODP-based sources within your BW system into local tables (file) in the SAP Datasphere system of your SAP Business Data Cloud formation. In the following chapters both options are described:

1.1) Exposing an InfoProvider of SAP BW/4HANA via the Data Product Generator (in SAP BW/4HANA Administration Cockpit)

Establish a subscription in SAP BW/4HANA Administration Cockpit, select the InfoProvider which needs to be exposed to the ObjectStore and activate the subscription:

(remark: "CF in thge description of the objects in the screenshots is referring to the scenario of the exercise and means "Cash Flow")

Regular transfers can be scheduled from the subscription using a BW Process Chain. With every execution of the BW Process Chain the data is pushed into the SAP Datasphere object store. There is a new Process Type available to be used to propagate the data of an InfoProvider to the ObjectStore "Load Process and Postprocessing - Data Subscription":

The status of the latest execution of a subscription can be checked in the subscription overview:

For each subscription the local table can be viewed as well as its content. By pressing "View Local Table" for a given subscription you will be guided to the Datasphere instance and the respective local table in the Data Builder. From here the content of the table can also be checked.

1.2) Exposing an InfoProvider of SAP BW/4HANA via the Scenario Generator (with the SAP BW/4HANA Modeling Tools in Eclipse)

With the SAP BW/4HANA Modelling Tools in Eclipse 1.27 there is an additional possibility to expose a BW InfoProvider to the Object Store of SAP Datasphere. Eitherway, regardless which option is used, the local table (subscription) has to be used as a basis in the Data Sharing Cockpit to generate a Data Product.

There are three important concepts which neeed to be considered using the Scenario Generator:

A 'scenario' is a list of references between data subscriptions which are required to reconstruct a specific BW model (such as a DataStore object (advanced) (aDSO) or a CompositeProvider (HCPR)). For example, if you have a CompositeProvider, you would not only need a data subscription to represent the top-level object, but also further data subscriptions for the InfoObjects it contains and other dependencies.

The 'scenario tree' saves these dependencies between the objects in the BW model, as well as the equivalent data subscriptions and their dependencies. It also considers existing data subscriptions for dependent objects to avoid the creation of duplicate data subscriptions and local tables (file).

The 'Scenario Generator' lets you not only create scenarios out of your BW models, but also mass generate the associated data subscriptions out of the scenario tree. Through this you can replicate an entire BW model into local tables (file) in your SAP Datasphere tenant in SAP Business Data Cloud. There, the extracted data and associated semantics are stored in table format and become available for further use cases, such as creating data products or sharing to SAP Databricks.

So the basic workflow in the Scenario Generator is:

a) To create a Scenario which is a collection of all Objects belonging to a given BW InfoProvider and their dependencies. For example a CompositeProvider alone does not contain any data. The data is coming from its PartProviders so a scenario of a CompositeProvider would also include the PartProviders.

b) Generate the subscriptions which consists of the lokal tables and the mechanisms to replicate the data from the InfoProviders to the local tables

As a basis for the Data Product to be created this time the CompositeProvider (DPG_CP_CF) from the scenario above is taken. In the Scenario Generators first tab 'Scenario Core Objects' some general settings can be made before collecting the objects related to a selected InfoProvider to create the scenario and the dependency tree of all objects belonging to the scenario.

'Selection Grouping' defines which related objects shoud be collected for a selected BW InfoProvider. It can be specified that 'only necessary' objects are taken into consideration or also the Upstream and downstream objects along the Dataflow of the InfoProvider.
The 'Association Levels' define the amount of levels included in the dependency tree.
There are some optional checkboxes to activate the possibility to transport subscriptions or to consider already existing subscriptions to prevent duplicates and redundant subscriptions on objects where a subscription already exists.

After pressing the 'Collect' Button, all dependent objects from the CompositeProvider are collected which are the Inbound ADSO as the only PartProvider and the second Object collected is the InfoObject 'Company Code' which is the only real InfoObject in the Inbound ADSO (rest of the columns are fieldbased).

After the collection of the objects the relationsships are displayed in the Tab 'Object Relations'. In this list all subscriptions which are generated in this second step can be seen and the generation of the subscription triggered. After this the 'Message' tab is shown where all relevant messages from the generation process can be seen.

2) Creation of a DataProduct out of the exposed SAP BW/4HANA ADSO

To create a DataProduct from the local table the Data Sharing Studio from Datasphere must be used. In a BDC Formation there can only be one Datasphere System assigned to the BW 7.5 or BW/4HANA instance.

Before the DataProduct can be generated, a Data Provider Profile must be defined (or an existing one used) where the mandatory flag "Data Provider Visibility" is set to "Unified Customer Landscape Formations".

Now a new DataProduct can be created (Data Sharing Cockpit > My Data Products > Create Product)

In the definition of the DataProduct the fields for the Contexts and Deliverymode are automatically taken from the Data Provider Profile and to connect to the right ADSO the corresponding Datasphere Space needs to be specified where the ADSO is located:

After saving the DataProduct it should be available in the overview table under "My Data Products". By selecting this entry in the table the Status can be switched to "listed".

3) Next Steps

Optional: create a graphical view to bring the data of this newly created DataProduct together with the Working Capital / Chash Flow data which is already available from the exercises before.

You can also now continue with the reading material that is provided about accessing Data products from customized S/4HANA CDS views.

4) Important Links / Notes

Pre-requisites

SAP Note [3590400 - Configuration SAP BW and SAP BW/4HANA: Data Product Generator for SAP Business Data Cloud] (https://me.sap.com/notes/3590400)
SAP Note [3590318 Pilot BW Configuration for Data Product Generator in SAP BDC] (https://me.sap.com/notes/3590318)
SAP Note [3593519, TCI2 for BW on HANA, BW/4HANA] (https://me.sap.com/notes/3593519)
SAP Note 3581186 - OA2C: RFC API
SAP Notes for Transaction SOAUTH2_CLIENT:
3532137 - OA2C: Dynpro UI for OAuth2.0 Client Configuration
3561719 - OA2C: New dynpro UI SOAUTH2_CLIENT, generation of DDIC object
3561640 - OA2C: Token Status for SOAUTH2_CLIENT
3692414 - Data Subscription TLOGO: After TCI 3.0
Supported Releases of SAP BW 7.5 / SAP BW/4HANA:
SAP BW 7.50 SP24 onwards
SAP BW/4HANA 2021 SP4 onwards
SAP BW/4HANA 2023 SP0 onwards