Why SAP's Business Data Cloud Changes Everything About Enterprise Data
Mohammed Mubeen
Principal SAP Data & Analytics Architect | Presales & Solution Strategist | SAP Datasphere, SAC, BDC, BW/4HANA | Enabling Cloud-Driven Innovation
"Only in God may we trust. The rest bring Data." This quote perfectly captures the new reality for enterprises: data is the foundation of trust, insight, and innovation. As SAP unveils its Business Data Cloud (BDC), we stand at the crossroads of a data revolution—one that moves beyond warehouses and lakes to a world of agile, productized data, ready for AI.
Four Truths from the Multiverse of Data
Data Fabric and Data Lakes killed the Data Warehouse concept.
Data Mesh is the next evolution, building on Data Fabric.
Dashboards are now generated on demand with GenAI—rigidity is gone.
SAP’s BDC unifies Fabric, Mesh, Dashboards, and GenAI in a single vision.
A Brief History: From BW and BO to the Cloud
For years, SAP BW (Business Warehouse) and Business Objects (BO) were the backbone of enterprise analytics, centralizing data and enabling robust reporting. While these tools empowered organizations, their on-premise, rigid nature struggled to keep pace with the demands of modern, agile business.
The rise of cloud, big data, and real-time analytics shifted the focus to platforms like SAP Analytics Cloud and S/4HANA embedded analytics. Hyperscalers and modern data platforms (Snowflake, Databricks) embraced flexibility and scale, introducing the Medallion Architecture—a multi-tiered data lakehouse model (Bronze, Silver, Gold) that improved organization and quality but still left business users waiting for curated data.
Medallion Architecture: Progress and Pitfalls
Medallion’s multi-hop approach organizes data through validation and transformation stages, ensuring quality and integrity. However, it’s fundamentally a pull mechanism:
Business users must wait for data to reach the “Gold” layer before insights are possible.
Errors in early layers can propagate, and the lack of business context in upstream tiers limits agility and relevance.
Data is treated as a technical artifact, not a business product—causing inefficiency and bottlenecks.
The Data Mesh and Data Product Revolution
The Data Mesh model addresses these challenges by decentralizing data ownership and treating data as a product—shaped, refined, and packaged for specific business needs.
Key Principles:
Domain-oriented ownership: Data responsibility lies with teams closest to the business.
Data as a product: Data is discoverable, understandable, trustworthy, and accessible.
Self-serve platforms: Domain teams build and deploy data products independently.
Federated governance: Balance standards with domain autonomy.
What is a Data Product? A data product is more than a dataset. It’s a self-contained package—data, metadata, code, and infrastructure—designed for a specific business purpose. It’s technology-agnostic, discoverable, and focused on solving real user problems. Like software, it’s built, marketed, and supported for adoption and value.
SAP’s Journey: From BW to Business Data Cloud
SAP has always been a data leader—from BW in 1998 to HANA, Data Warehouse Cloud, and Datasphere. With the launch of SAP Business Data Cloud (BDC) in 2025, SAP brings together BW, Datasphere, and Analytics Cloud in a unified, cloud-native platform.
What’s new?
Out-of-the-box data products built on harmonized models.
A strong focus on data products as the building blocks of analytics and AI.
Alignment with Data Mesh principles: decentralized, productized, and governed.
Why Data Products Matter for AI and LLMs
Large Language Models (LLMs) and GenAI need more than raw or cataloged data—they need context, relationships, and business meaning.
Unorganized data pools: LLMs struggle to generate efficient queries and accurate results.
Organized catalogs: Help, but still lack deep business context and require constant maintenance.
Data products solve this: They provide LLMs with structured, contextualized, and business-ready data—enabling accurate, relevant, and actionable insights for enterprises.
The Future: Agile, Productized, AI-Ready Data
As every company becomes an AI company, the ability to link business understanding with strategic choices becomes vital. SAP's Business Data Cloud, with its focus on Data Products, represents a fundamental shift from managing data to leveraging it strategically.
The future belongs to organizations that can bridge the gap between data and business value. And that future is arriving faster than most realize.