It’s been almost 20 years since data scientist Clive Humby made the proclamation that “Data is the new oil”. This could not be more true today. When used effectively, data has the ability to provide companies with critical insights into operational performance, resource allocation and other strategic drivers – all of which need to be utilized in the ever-present goal of competitive advantage.
Unlike oil, however, sources of data are growing rapidly, and the overall amount of information used by organizations has exploded exponentially. In the Life Sciences industry, this is especially true with systems capturing a host of critical information such as patient data, clinical trial results and regulatory submissions adding to an already vast array of data sources.
In advising our Life Science clients, we have seen how fragmented data landscapes can severely impact critical operations, particularly within clinical trial management, where harmonized and trusted information is essential to optimizing supply planning, patient allocation, and trial execution timelines. Like oil, the storage and management of this data is of vital importance and is needed to drive innovation across research and development, supply chain efficiency and commercial effectiveness, all of which contribute to the ultimate goal of improving patients’ lives.
With this abundance of data, Life Science organizations struggle to bring context, consistency, and trust to their information. Today there exists a variety of cloud and on-premise tools and architectures which aim to bring order to this chaos. But too often this has seen an increase in data silos, fragmented governance and the unwanted multiple versions of the truth. Rather than solving the challenges of low trust, low user adoption, and even slower decision making, these often intensify them.
Introducing SAP Business Data Cloud: The Life Science data engine that could
Enter SAP Business Data Cloud (BDC), SAP’s latest data and analytics platform. It’s purpose-built to bring together disparate source systems and analytic platforms into a single governed landscape that enables organizations to derive insights without duplicating data or redefining business logic. SAP BDC bundles together the established data modelling functionality of SAP Datasphere or BW PCE (private cloud edition) and the robust dashboarding and visualization capabilities of SAP Analytics Cloud with a new customer insight experience in the form of Intelligent Applications. What does this do? It enables the adoption of ML/AI capabilities and data engineering with SAP Databricks.
Each component complements one another to ensure governed and trustworthy analytics. Plus, they are fully optional, ensuring customers have their choice of adoption while being supported by the fact that the single semantic layer provided by SAP BDC ensures continuity of experience by end-users. What’s more, customers can adopt what they need and integrate what they already have.
Alongside the integration of existing technologies, SAP BDC comes with the enablement of new technological innovations to support analytics, including the facilitation of Delta-Share capabilities. This means that when accessing data from source systems, a zero-copy approach is used where data is no longer replicated but is instead accessed in real-time – ultimately saving time and data storage costs. The AI trend is also both embedded and facilitated with SAP’s conversational AI copilot Joule, offering instant analytics insights and code completion support while AI/ML scenarios can be developed and exposed to analytics use cases.
Since its announcement in February 2025, SAP has continued the cloud data democratization revolution with further partnerships with Google, Microsoft and now Snowflake. Each allows SAP BDC to extend the zero-copy functionality across Google BigQuery, Microsoft Fabric and Snowflake through the SAP Business Data Cloud Connect utility. The results? SAP can open its ecosystem further to customers who have an established analytics architecture in other domains; and they can make the most of SAP BDC’s functionality without writing off the sunk cost of earlier investments.
Additionally, like SAP Databricks, there now exists the SAP Snowflake addon – giving customers their preferred data engineering and ML platform to extend their data landscape.
Clarity from complexity: SAP BDC for Life Sciences
In the Life Sciences industry, organizations negotiate data landscapes complicated by extremely high volumes of highly regulated data that have strict auditability and validation requirements. This information is often fragmented across functions (clinical, manufacturing, R&D etc) and stored in a variety of different platforms, each utilizing their own standards and unique metadata. For example, making educated quality control decisions based on bringing together batch records, quality control results, and deviation data often requires combining information from MES, LIMS, ERP, and QMS systems that use different data structures and master data definitions.
The ability of SAP BDC to bring together data from disparate sources into a single governed platform creates semantic consistency across data domains such as clinical, quality and supply (which supports consistent, reusable analytics solutions across functions). Being encompassed in a unified platform facilitates visibility into data lineage which is critical for regulatory compliance and audit readiness.
By adopting and embracing SAP BDC, Life Sciences companies gain the ability to truly achieve a single source of truth from which analytics can be trusted by stakeholders, and meaningful insights can be derived. The focus by SAP on Data Products within SAP BDC directly addresses the industry trend of Data Mesh. This enables domains, such as clinical, quality or supply, to own their decentralized data products while still under a centrally governed framework. This also improves reusability for data engineers and accelerates development across functions.
Furthermore, these data products can be exposed to end users in the form of semantically rich AI enabled Intelligent Applications. These not only provide live data to users but also surface automated insights and recommendations that would previously require complex manual analysis.
Tenthpin & SAP co-innovating towards analytical excellence
At Tenthpin, we have a rich history of collaboration with SAP, bringing our deep cross-domain Life Sciences expertise and SAP competency into:
- Client engagements
- Co-innovation of SAP products
- Strong roadmap influence
- Development of industry-focused accelerators and best practices
In the world of Data and Analytics, this has led to the creation of extensive value adds and product development, including our Life Science Analytics Suite providing insights across the SAP products of ICSM, BRH and CGTO.
And right now, we’re entering a new stage of our relationship, becoming the key partner for SAP Business Data Cloud for the Life Sciences Industry. Already assisting many customers achieve their SAP analytics ambitions, we will be supporting the Life Sciences ecosystem with advisory, architecture, and implementation services that accelerate the adoption of SAP BDC and unlock measurable value for SAP customers.
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This article is part two of a multiple-part series. Check part one here.
