Why An Effective AI Strategy Needs SAP Business Data Cloud

Enterprises are rapidly adopting Artificial Intelligence into everyday business while systems are adapting to incorporate the same. However, any AI is only as powerful as the underlying data. SAP recently launched the Business Data Cloud (BDC) to address the complexity of ERP data being leveraged to drive efficient AI. This solution enables enterprises to efficiently leverage SAP and non-SAP data into a single harmonized data layer powering Data, Analytics and AI.

Christian Klein, CEO of SAP said during the launch of SAP BDC that this solution is how enterprises turn mission-critical data into intelligent applications and outcomes securely, at scale, and with business context intact.

The Evolution of Data Fabric

Over the past decade, data architectures have moved from centralized data warehouses to more federated and distributed paradigms like data lakes, data lakehouses, and data meshes. This has been necessitated due to the ever-rising volumes, diverse data types, and the need for faster analytics cycles across domains. The concept of a data fabric has recently emerged to drive, automate and orchestrate data and analytics delivery across hybrid and multi‑cloud landscapes while preserving semantic meaning and policy controls end to end.

SAP’s perspective of the data fabric emphasizes on keeping business context in adherence to data as it flows. This ensures the common problem of context being lost through replication or ad‑hoc pipelines, which degrades analytics and eventually AI quality downstream.

Introduction To Business Data Fabric

SAP S/4HANA, a system of records, houses business data structured around a complex data model. The business data fabric augments the data fabric concept with a semantic layer that encapsulates data, dimensions, and relationships from SAP ERP, ensuring that analytics, planning, and AI consume context‑rich data products rather than raw tables. SAP positions BDC as a fully managed SaaS that unifies SAP and third‑party data, connects to an open ecosystem, and delivers intelligent applications on top, so lines of business make decisions with governed, contextual data.

Data is also a core component as SAP evolves to the Business Suite paradigm where AI and analytics are embedded into business processes.

Components Of SAP BDC

SAP BDC brings together multiple capabilities to enable the enterprise business data fabric. This includes data discovery, data engineering and modelling along with data visualization. This is supported by capabilities in data governance, cataloguing and lineage. Additionally, SAP BDC also enables enterprise planning with SAP Analytics Cloud. It integrates with SAP Databricks to blend contextual SAP data with non‑SAP sources in an open data ecosystem, encouraging zero data copy and excessive replication while enabling AI/ML workloads at scale.

Moreover, intelligent applications and AI services use trusted data products and the semantic layer to automate and learn in real time across finance, supply chain, and people processes, turning data into operational outcomes.

The key components of SAP BDC are highlighted in the figure below:

Fig 1: SAP Datasphere components

1. SAP Datasphere:

This is the central technical foundation of SAP BDC, providing a unified environment for data integration, data warehousing, and data governance across various data sources.

2. SAP Analytics Cloud (SAC):

SAC delivers advanced analytics, reporting, and enterprise planning capabilities, offering real-time insights powered by AI and machine learning.

3. SAP Databricks:

Through its partnership with Databricks, SAP BDC enables advanced data science and machine learning on both SAP and third-party data, facilitating data sharing and model training.

4. Intelligent Applications (or Insight Apps):

These are ready-to-use applications and data packages, managed by SAP, that provide standardized business data for specific scenarios, reducing the effort to build and run analytics applications.

5. SAP BDC Cockpit:

This is the centralized user interface that administrators use to manage and orchestrate the entire SAP BDC environment, including configuring landscapes, managing data artifacts, and activating data products.

Foundation Services & Data Products in SAP BDC

Apart from these, SAP BDC features foundation services and data products that are the building blocks for data products and services. They are structured, governed data assets designed to accelerate analytics and AI use cases. They include:

1. SAP BW/4HANA PCE (Private Cloud Edition):

This component supports customers with existing investments in SAP Business Warehouse, offering a migration path to the BDC platform.

2. Unified Semantic Layer:

A crucial element that standardizes data definitions across different systems, ensuring consistency and enabling unified business semantics.

3. Data Products:

Standardized, governed data assets provided by SAP and activated via the Foundation Services, which simplify data access and utilization.

Implementation Use Cases

SAP BDC finds multiple use cases across Line of Business functions primarily due to its ability to connect and process data.

Finance leaders can accelerate Planning and Analytics use cases by unifying actuals and plans in SAP Analytics Cloud, consuming curated data products from SAP BDC to analyze profitability, working capital, and scenario impacts with governed semantics for accounts, entities, and time.

Supply chain teams can connect planning, procurement, logistics, and operations to enable resilience, ingesting SAP and partner data into the fabric, running ML‑driven predictions, and closing the loop with intelligent apps that trigger actions back into operational systems.

People analytics can combine HR data with skills and third‑party benchmarks to inform talent decisions, leveraging prebuilt intelligent applications that shorten time‑to‑value beyond dashboards and into guided decisions:

1. Greenfield Business Data Fabric: SAP BDC enables the creation of standardized, high-quality data products that serve as the foundation for a unified business data fabric, supporting intelligent applications and tailored analytics across the enterprise.
2. SAP BW modernization: SAP BDC provides a path to migrate existing SAP BW systems to a cloud-native architecture, allowing for the reuse of existing SAP BW data products within a zero-copy approach and integrating them with Databricks for advanced AI/ML use cases.
3. Datasphere upgrade: Datasphere, which is still a key component of SAP BDC can be easily upgraded to the latest technology. However, currently this option is still under guidance from SAP.

Benefits and Challenges

While SAP BDC brings about a key milestone in the journey towards building a cloud data foundation and brings about multiple benefits:

• A key advantage is preserving business context to improve trust and relevance for analytics and AI.
• Rebuilding business context is a tedious process and could incur hidden costs of extracts/replication. However, SAP BDC with its curated data products accelerates time‑to‑value with intelligent applications and partner solutions in an open ecosystem.
• Organizations also benefit from democratized access through a governed semantic layer, enabling real‑time decisions while decoupling business logic from storage and compute choices.

Still, SAP BDC comes with its own set of challenges that include:

• Changes to operating model shifts to data product ownership
• harmonizing SAP and non‑SAP semantics across domains
• Change management

A primary challenge is for teams moving from report‑centric workflows to productized data and applications, which the SAP BDC roadmap aims to mitigate through managed services and deep application integration.

Roadmap and Future Plans

SAP indicates BDC as the path forward for SAP BW customers by moving to Private Cloud and converting BW objects to Data Products. Adopting the latest data and AI capabilities, including bidirectional data sharing and machine learning, as part of modernization to the cloud enables customers to upgrade rapidly to the next gen data foundation. Existing Datasphere and Analytics Cloud customers can continue uninterrupted, with options over time to transition into the fully managed Business Data Cloud footprint.

Finally, SAP BDC enables customers to move from legacy BW to the next gen data landscape. This not only enables customers to develop a robust data foundation but also enable downstream AI applications across the enterprise.