6 min read
The debate between SAP Datasphere and third-party data platforms like Snowflake is not an either/or ultimatum. The winning enterprise architecture preserves SAP’s rich business context and hierarchy logic while exposing clean data models to cloud analytic tooling.
The cost of stripping SAP semantic context
Raw table replication from SAP into cloud lakes strips away critical business logic—currency conversions, fiscal calendars, and master data hierarchies. Rebuilding this logic manually in external SQL scripts is extraordinarily expensive and error-prone.
Federation over physical duplication
Modern data architectures leverage SAP Datasphere to query ERP data virtually in real time, preventing duplicate data storage fees and complex nightly ETL pipeline failures.
Enabling applied AI on trustworthy enterprise ground
Generative AI models and predictive algorithms are only as dependable as the data feeding them. Preserving governed SAP data semantics gives AI assistants the verified financial context required for automated forecasting.
About Cristina Bernardi
Head of Data & Analytics · Bonfire. Veteran SAP practitioner specializing in complex New Zealand enterprise delivery and strategic advisory.
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