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Go from search to discovery

When there are 100s of data sources and countless name conventions, searching can be tedious speaking their own languages. Discovering related data instantaneously will help you leap from antagonizing searches to discovering insights.

Understand relationships

And not just tables. The relationships often matter more to the answers we seek than the data entries they connect. Understanding our processes and systems requires understanding our data real estate in its context.
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Better industrial AI initiatives

Knowledge graphs help operationalize your data science, artificial intelligence, machine learning (AI/ML), and Internet of Things (IoT) initiatives.

Cognite's powerful, built-in SQL transformation services automatically create resource types and build the industrial knowledge graph

Cognite Data Fusion is your tool to turn raw data into valuable operational insights

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Cognite Data Fusion staging area

Data flows from the extractor into Cognite Data Fusion ingestion API. From here on, everything lives in the cloud. Data is first ingested into the raw storage layer.
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Spark SQL queries

The transform step shapes and moves the data from the staging area into the Cognite Data Fusion data model. Cognite Data Fusion comes with a built-in transformation.
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Transform on schedules

The transformation tools, including monitoring services, run in Cognite Data Fusion and can be scheduled to run at specific intervals.
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Cognite Data Fusion open data model (industrial knowledge graph)

The transformation step can both turn raw data into Cognite Resource types and build their relationships to form the data model.

Recognized by the industry leaders and research community

What independent voices say about the value of data contextualization in populating the industrial knowledge graph

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Contextualized Data and Digital Twins Amplify Digitization Value

“Digitalization success hinges on providing data scientists and developers with access to contextual, meaningful data at their moment of need.”

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Cognite Data Fusion provides contextualization of operational asset data to increase ease of data analytics

“CDF uses a combination of machine learning, rules engines, and subject-matter expertise to create a pipeline of data tagging and labeling so that CDF knowledge graphs are automatically populated.”

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Verdantix Market insight: 10 applications of large language models for industry

LLM-based information retrieval systems give operators concise, relevant insights for a big-picture view – helping them discover inefficiencies and safety risks.

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