Grundfos Builds a Scalable and Governed Data Foundation with VaultSpeed
Industry:
Manufacturing
Use Case:
Preparing Data Vaults for AI
Platform:
Snowflake
Technologies:
Data Vault 2.0, ERP, CRM, PLM, IoT Platforms
60
countries
500+
active users
3
FTE saved
190+
procedures
Grundfos is a global leader in advanced pump solutions and water technologies, operating in more than 60 countries and delivering millions of units annually across commercial, industrial, and utility markets. Known for its commitment to innovation and sustainability, the company launched an initiative to build a modern, governed data foundation capable of supporting global scale while enabling reuse across product development, operations, sales, and customer engagement.
The Challenge: Scaling Data Products Across a Global Landscape
Grundfos manages a highly complex data landscape. Product selection and configuration platforms play a critical role in commercial success. IoT-enabled pumps generate large volumes of telemetry data. ERP, CRM, and PLM systems support core global processes across regions and business units.
As the organization continued to grow, including planned expansion in China, existing data practices became a limiting factor. Data was fragmented across teams and geographies. Manual processes slowed delivery and introduced errors, particularly in product data management. Teams lacked standardized modeling layers that could support analytics, artificial intelligence, and consistent reuse. Delivery timelines varied significantly and often depended on custom development, making it difficult to scale data products efficiently across markets.
Grundfos needed a data foundation that could support high-volume processing, enable reuse across initiatives, and enforce governance without slowing down delivery.
The Approach: Model-Driven Automation with VaultSpeed
To address these challenges, Grundfos selected VaultSpeed as a core component of its modern data stack. VaultSpeed introduces a metadata-driven and model-driven approach to data automation, replacing custom, manually maintained pipelines with standardized and reusable building blocks that scale across teams and regions
By focusing on modeling business concepts rather than hand-coded transformations, VaultSpeed enables consistent data structures across domains while reducing engineering effort. Governance is strengthened through improved lineage and integration with Collibra, ensuring that data products remain transparent and traceable as they scale.
This approach allows Grundfos to industrialize data product delivery while maintaining control and consistency across teams and regions.
Applying the Approach Across Key Data Initiatives
VaultSpeed was applied across several strategic initiatives, enabling the same standardized data product patterns to be reused where scale, consistency, and governance were essential.
The Product Catalogue initiative supports product search, configuration, and selection by integrating data from ERP, CRM, and PLM systems. VaultSpeed automates the modeling of product specifications, configuration logic, availability rules, and customer segmentation, reducing the manual effort required to manage this complex domain.
The Insights Engine manages product data used across web and e-commerce platforms. VaultSpeed ensures that this high-volume data is modeled consistently, enabling reliable analytics and stable downstream consumption.
The Nightsky Data Catalogue provides internal access to commercial, customer, and sales data. By reducing backend data preparation work, VaultSpeed enables teams to deliver insights more efficiently. Grundfos describes this shift as building data products once and reusing them across the organization.
Within IoT and iSolutions Cloud initiatives, smart pump sensor data is combined with governed master data models. VaultSpeed supports the transition away from spreadsheet-driven workflows toward standardized data structures that feed Power BI dashboards and operational analytics, improving data quality and accelerating decision making.
The Operating Model: Enabling Autonomy with Governance
Delivering these initiatives required more than new technology. It required a change in how teams worked together across domains. VaultSpeed introduced a model-driven workflow that enabled faster delivery while enforcing governance by design.
Teams gained the ability to produce their own data products within a centrally governed framework, because standardization and governance are enforced through models rather than manual coordination. Standardized patterns could be reused across regions and projects, reducing duplication and improving consistency. Automation became a foundational part of how data products are delivered at Grundfos, rather than an isolated optimization.
The Impact: From Standardization to Business Value
As a result of this modernization, manual effort has been significantly reduced and delivery has become more predictable. Data models and pipelines are more consistent across domains. Product-centric data products now support multiple business functions, strengthening both operational processes and analytical capabilities.
Reusable modeling patterns allow teams to deliver new data products more quickly, while governance has improved through standardized structures and end-to-end lineage generated automatically from the model. VaultSpeed plays a central role in enabling these outcomes by automating modeling and pipeline generation in a way that scales across teams and markets without sacrificing quality or control.
The Takeaway: Building Once and Scaling Everywhere
Grundfos has established a data foundation designed for global scale, reuse, and governance. By adopting a model-driven and automated approach with VaultSpeed, the company has moved away from fragmented, manual data practices toward an operating model that supports consistent data product delivery across regions and initiatives.
For organizations facing similar scale and complexity, this shows that reusable data products only become sustainable when automation is model-driven and governed by default.

