The energy sector is at a pivotal moment. Leaders are tasked with modernizing aging infrastructure to redefine how the world is energized in a lower-carbon future. To succeed, they need more than just data storage; they need actionable, reliable intelligence that spans the entire enterprise.
This is why Cognite is proud to support the launch of Snowflake’s new Energy Solutions. By combining Snowflake’s AI Data Cloud with Cognite’s specialized ability to make complex industrial data AI-ready and scalable, we are finally enabling customers to unify IT and OT workflows across the enterprise.
The Challenge: Warehousing operational data
Snowflake is one of the premier platforms for enterprise data warehousing and business intelligence. However, industrial data—high-frequency time series, 3D models, and interactive P&IDs—present a unique challenge. It is voluminous, messy, and lacks the context that business analysts need to make sense of it.
Without a specialized intelligence layer to interpret this data, energy companies often end up with swamps of raw OT data that remain fragmented and unusable for high-fidelity AI insights. This prevents organizations from answering critical questions, such as calculating the true cost of downtime or predicting asset failure with precision.
The Solution: Persistent Contextualization
To solve this, Cognite acts as the Industrial System of Intelligence. We ingest and persist raw industrial data within the Cognite AI and Data Platform, transforming it into a real-time, unified Industrial Knowledge Graph.
Some enterprise architects argue for data federation—querying source systems on demand—to avoid copying data. However, as Cognite Field CTO Jason Schern explains, federation often fails at an industrial scale.
"Federation can work well in limited, low-frequency use cases," says Schern. "But at an industrial scale, data federation often creates bottlenecks."
By persisting data, Cognite enables real-time access and rich context that federation cannot match. This approach optimizes storage for specific data types (like time series), ensuring sub-second access to trillions of data points without burdening the budget. This "persistent contextualization" is the critical step that makes raw data AI-ready.
Zero-Copy: The Best of Both Worlds
Once the data is contextualized and persisted in Cognite, how do we get it to Snowflake users without creating new silos? The answer is Zero-Copy Data Sharing.
Instead of building complex and often costly ETL pipelines to move data back and forth, Cognite leverages open standards to grant Snowflake users direct, read-only access to our Industrial Knowledge Graph.
- For the Data Scientist: They get instant access to clean, governed industrial data directly within their familiar Snowflake environment.
- For the Architect: It eliminates data duplication and reduces the "integration tax" of maintaining custom pipelines.
- For the Business: It accelerates time-to-value, enabling cross-domain use cases that fuse financial data (in Snowflake) with operational data (in Cognite).
Powering the Future of Energy
This partnership is about meeting customers where they are. By bringing Cognite’s deep domain expertise into the Snowflake ecosystem, we empower energy organizations to break down the barriers between the boardroom and the plant floor.
Whether it’s improving asset health, ensuring regulatory compliance, or driving net-zero goals, Cognite and Snowflake provide the unified data foundation necessary to turn ambitious energy strategies into operational reality.