A Gradual Approach Instead of a Big Bang: Pragmatically Evolving SAP Data Architecture
A Gradual Approach Instead of a Big Bang: Pragmatically Evolving SAP Data Architecture
Offload SAP BW and integrate it seamlessly into new architectures
The introduction of SAP Datasphere marks a fundamental shift in SAP data management: away from a purely centralized data warehouse toward integrated, cloud-based architectures. For many companies, this is not about completely replacing their SAP BW, but rather about its targeted further development and a focus on core tasks.
In our webinar on June 30, 2026, at 10 a.m., we’ll show you exactly what the so-called “BW Diet” entails and what options it offers. Using typical scenarios, we’ll demonstrate how SAP BW can be effectively integrated into a modern data architecture—without a big-bang transformation.
The focus of the webinar:
- Understanding SAP Datasphere: The Role of the Cloud Platform in Modern Data Management and Its Interaction with SAP BW.
- The "BW Diet" Concept: How to specifically reduce pressure on mature BW landscapes and focus them on their core functions.
- An Overview of Architectural Approaches: Hybrid, Add-on, and Transformation Scenarios, and Their Practical Applications.
- Organization and Governance: The Impact of Data Fabric and Self-Service on Roles, Collaboration, and Data Ownership.
Learn how to eliminate unnecessary complexity from your SAP BW while paving the way for a modern data architecture. Discuss decision-making options, typical scenarios, and organizational implications—in a practical and structured manner.
Sounds exciting? Then register now for the free webinar:
Speaker
Julian Schütt has been advising our customers for over 15 years, from the conception to the implementation of smart data architectures. As head of the Data & Cloud Services business unit, he is involved in the use of innovative technologies, from agile cloud environments to the efficient use of artificial intelligence.
Thomas Laußer has been working in data engineering for more than 10 years and is now responsible for this area at celver. Together with his team, he is shaping the future of data platforms. He has accompanied the transition from traditional to modern data engineering and is therefore familiar with the needs and requirements of companies that are embarking on this path or have already arrived there and want to reach the next evolutionary stage.
