ERP-1045 - Datasphere foundation build for S/4 - S2S FS in Progress
The DDFS covers the end to end datasphere data flows for S2S area. The sub area it covers include EHS - Environment, Health & Safety , PRC - Product Compliance, SCT - Sustainability Control Tower and SFM - Sustainability Footprint Management. Below are the details on each sub area and KPIS it will cover:
| Sub-Area | Details | Example KPIs | Comments |
|---|---|---|---|
| EHS - Environment, Health & Safety | The SAP EHS (Environment, Health and Safety) module is designed to help organizations capture, analyse and communicate safety, environmental and compliance data in a structured way. At its core, SAP EHS reporting consolidates data from different subcomponents like incident management, occupational health, product safety, and environmental compliance into meaningful outputs for both operational and regulatory use. | Emissions, waste, and resource usage (air, water, energy), tracking workplace incidents, near misses, injuries, and illnesses | |
| PRC - Product Compliance | The SAP Product Compliance (PRC) is part of SAP’s EHS and product stewardship portfolio. From a reporting perspective, its main role is to ensure companies can track, document, and report regulatory compliance data for products across global markets. It is created as a separate sub-module in datasphere considering the authorisation rules to only provide a sub-user group access to this data. | Compliance reporting, SVT, SVHC, Substance & Composition Reporting | |
| SCT -Sustainability Control Tower | SAP Sustainability Control Tower (SCT) is designed to centralize, standardize, and automate ESG (Environmental, Social, Governance) data reporting across an organization. It enables automated, compliant and audit-ready sustainability reporting. SCT relies on SAP datasphere for data foundation and scalability. SAP Datasphere acts as the data layer beneath SCT. It integrates data from various SAP and non-SAP sources, models and harmonizes this data before it reaches SCT. This integration happens via SAP supplied DPI (Data Provisioning & Integration). | Emissions, Energy, Water Management, Waste, Social KPIs, Carbon Credits, Financial KPIs | |
| SFM - Sustainability Footprint Management. | SAP Sustainability Footprint Management (SFM) is a cloud-based solution designed to calculate, analyse, and report product and corporate level carbon footprints. From a reporting perspective, its value lies in turning complex emissions data into structured, auditable and decision ready outputs. Datasphere will be used to send some of the already consolidated data (like waste) and also to extract the footprint data to be used in reporting. | Product Carbon Footprints (PCF) per product and supplier |
The models covered under this DDFS will cater towards requirements from the following Jira Requests -
Standard extractors do not need to be documented unless extended.
Where custom extractors / extensions are required, reference the FSD for that enhancement.
| Extractor Name | Details | Build Jira Ref For Extension Information |
|---|---|---|
| /SYQ/C_WasteTransportDocument | CDS view on top of 'I_WasteAnalyticsDimension' with associations created similar to 'I_WasteAnalyticsCube'. This view will be extraction and delta enabled. | |
| /SYQ/C_* | A custom CDS view on top of a table (name to be confirmed) to extract emissions threshold information. | |
No transformations to be applied in the inbound layer for the sources from S4 systems.
A 2 year history (.csv) file for waste data will be provided by Syniti and uploaded into this table. The layout of the file is still under discussion and will be confirmed during the functional specification stage. Syniti will be responsible for all data mappings and validations and the file provided will be uploaded as is in datasphere. No transformation to the base file is required in datasphere.
The ESG reporting for Syensqo is done via Serf Codes. The waste transport document is the main controller of the waste KPIs, it contains R&D code which are mapped to Serf Codes. Further the serf codes are classified into categories which help to classify waste into disposal or recovery types. The mapping file will be provided by the functional consultant, which will be then uploaded into this table.
Below are the columns from the mapping file,
The ESG reporting for Syensqo is done via Serf Codes. The EM module will hold all the input and calculated amounts for water management against various Serf Codes. A subset of these Serf Codes are only required by SCT and it will be configured using this table as a control for mapping what needs to be sent to SCT from Datasphere.
Below are the columns and values for the table,
Data Collection Name/Serf Codes | Use Type | Stress Category | Water Source | Water Usage | Discharge Type | Water Losses(Custom Dimension) |
|---|---|---|---|---|---|---|
E74000 | C | Evaporative water losses | ||||
E74010 | C | Non-evaporative water losses (leakages) | ||||
E74020 | C | Water incorporated into end products | ||||
E74030 | C | Water incorporated into waste materials | ||||
E113070 - AI | C | STRESS_CAT_05 | ||||
E74040 | R | Cooling | ||||
E74050 | R | Process Water | ||||
Calc | C | |||||
E113078 | W | Z_SOURCE_08 | ||||
E113065 - AI | W | Z_SOURCE_07 | ||||
E113065 - AI | W | STRESS_CAT_04 |
The ESG reporting for Syensqo is done via Serf Codes. The EM module will hold all the input and calculated amounts for air & water emissions against various Serf Codes. A subset of these Serf Codes are only required by SCT and it will be configured using this table as a control for mapping what needs to be sent to SCT from Datasphere.
Below are the columns and values for the table,
This is still under discussion with S2S consultants.
Each 2TL* table in the Harmonisation layer will be populated from the corresponding 1TL* tables for each source system (RoW and China).
A Source System Identifier will be included as part of the primary key in the 2TL* tables to uniquely distinguish records originating from different source systems.
Join EHS Amounts (from EM) with Data Classification data to create a reusable view for periodic amounts against various classifiers used in EM. This will provide contextual data combining amounts against serf codes.
LHS: 2TL_S4HARM_C_EHSAmountDex
RHS: 2TL_S4HARM_SYQI_EHSDataCollectionClsfrDex
Join Field: EHSAmountSourceUUID to DataCollectionUUID
Join type: Left outer join
Cardinality: 1:n