SAP Datasphere

Outdated technology in use in the Business Intelligence (BI) sector 

Lack of resources in the BI sector 

Need to integrate multiple source systems and interfaces (third-party tools) 

Cost pressure and budgeting requirements 

Need to integrate BI systems into existing business processes 

Lack of clarity regarding the integration of artificial intelligence functions / machine learning in BI systems 

Strategic data architecture consulting (roadmap) incl. evaluation​

Identification of optimization opportunities 

Design of a future-proof SAP Datasphere landscape architecture​ 

Design of data models and flows using the latest SAP Datasphere functions and technologies 

Integration of external data sources 

Ensuring data quality and implementing governance measures. 

Training employees in the use of the new SAP Datasphere 

Improved performance through faster processing 

Better options for scalability of analytics solutions 

Cost efficiency gains through optimization of data models and processes 

Integration and consolidation by connecting different data sources 

Future-proofing by demonstrating AI integration options 

Optimization of data processing 

Best practices for data governance 

SAP S/4HANA system only provides rudimentary P&L reporting information. 

Data sources and integration requirements cannot be fully covered in SAP S/4HANA. 

Data quality and consistency is not always satisfactory. 

Definition of key figures is often unclear when considering them in P&L evaluations. 

Customization to business requirements is highly individual for companies. 

Report design and development are often confusing and not meaningful. 

User acceptance requires a clean solution design. 

Modeling in the SAP Datasphere on the basis of SAP S/4HANA sources 

Use and expansion of SAP Business Content 

Creation of an SAP Analytics Cloud Dashboard based on SAP Datasphere modeling 

Customization of the SAC dashboard “Profit & Loss” according to customer requirements 

Implementation of near real-time job scheduling for prompt data updates 

Optional if required: technical connection of SAP S/4HANA to SAP Datasphere (incl. authorizations) 

Improved quality of financial reports through clean data modeling 

Near real-time decision support on the company's financial situation 

Fast implementation of a company-wide P&L report 

Clear presentation through management dashboard 

Identification of trends and patterns by analyzing historical data 

Quick reaction to changes for decision-makers 

Effective performance management thanks to increased transparency