SAP S/4HANA Finance
Starter Kit for SAP Datasphere
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A Finance Data Product Ready for Use in 10 Days
In many companies, making financial data from SAP usable for reporting and planning still involves a significant technical effort: complex table structures, hierarchies, master data, and varying reporting requirements must be repeatedly adapted for new analytics scenarios.
The SAP S/4HANA Finance Starter Kit for SAP Datasphere significantly shortens this process: This compact implementation package creates a standardized finance data product that you can use as a central foundation for various analytics and planning scenarios. SAP financial data is integrated via approved standard CDS views, harmonized in SAP Datasphere, and made available uniformly through a central semantic layer. The S/4HANA core remains untouched. The Starter Kit follows the Clean Core principle and creates a reusable financial data architecture that can be expanded step by step.
Your current situation
- Financial data from SAP must be laboriously prepared time and again for reporting and planning purposes.
- Different reports and tools sometimes use their own data models and semantics.
- Balance sheet, income statement, and account hierarchies are modeled and maintained in multiple ways.
- Technical features of SAP, such as composite keys or time-dependent master data, increase the complexity.
- Reporting projects require a significant amount of time for data integration before they generate business value.
- As part of a "clean core" strategy, the SAP core should remain as free as possible from custom extensions.
What you get
- A preconfigured finance data product based on SAP Datasphere
- Connecting Your SAP S/4HANA System Using Published Standard CDS Views
- Harmonized finance semantics based on a bronze, silver, and gold layer approach
- Dynamic financial hierarchies for different balance sheet and income statement perspectives
- A central database for analytics, planning, and, in the future, business AI applications
- Open access to the data, for example in SAP Analytics Cloud, Board, or Microsoft Power BI
- Hands-on training for your team directly on your own system
- Ongoing remote coaching so your team can continue to develop the data product on its own afterward
Contents of the Starter Kit:
- Deployment & System Integration (5 PT):
Technical deployment of the Starter Kit in the target space, mapping of metadata, configuration and validation of the standard SAP CDS interfaces, and coordination of posting and controlling areas. - On-site Intensive Coaching (2 PT):
Day 1: Fundamentals, Architecture, the Medallion Approach, Data Builder, and Clean Core.
Day 2: Hands-on work on your own system with charts of accounts, posting logic, and financial hierarchies - Guided Onboarding & Remote Coaching (3 PT):
Flexible remote sessions for the targeted development of your finance data product, such as data model extensions, integration of consumption tools, customer-specific requirements, and architecture and modeling questions.
Your result:
Once you have completed the Starter Kit, you will not only have a technical template, but also a ready-to-use finance data product in SAP Datasphere that is connected to your SAP system and tailored to your environment. This allows you to establish a central finance semantics framework that you can reuse for various reporting and planning scenarios.
Instead of rebuilding data logic from scratch for each front end, various applications access the same underlying infrastructure. These include, in particular, SAP Analytics Cloud, Board, and Microsoft Power BI, as well as relational interfaces for other applications. This reduces repetitive modeling efforts, creates greater consistency across your analytics landscape, and lays the foundation for additional data-driven use cases.
Who is the Starter Kit designed for?
This offering is particularly well-suited for companies that:
- Implement SAP S/4HANA Finance,
- would like to establish SAP Datasphere as a central data and semantics layer,
- want to make financial data available more quickly for reporting and planning,
- further develop their SAP landscape according to Clean Core principles,
- reduce redundant data models and existing BI silos, or
- want to create a reusable database for future analytics and AI scenarios.

