Data contextualization

The advanced contextualization tools in Cognite Data Fusion® let you combine machine learning with a powerful rules engine and your domain expertise to map data from different source systems to each other in a custom data model.

Make data intuitively discoverable, understandable, and comparable independently of its origins, whether it reflects past, real-time, or simulated scenarios.

To apply generative AI in industrial environments, context means everything.

• Deep-dive into the link between Generative AI and data contextualization
• How to automatically contextualize and model OT, IT, and Engineering (ET) data
• Demonstrate practical use cases with Generative AI only achievable with contextualized data

80 to 90% is spent gathering and understanding the data, not building models and applications to create value.

Google estimates the time lost to 75% across industries.

• Within a typical asset, operational data is ingested from over 100,000 sensors, across more than 50 applications. Traditional efforts to connect data from systems are manual and time consuming.
• Rather than storing this data raw, unstructured data, Cognite Data Fusion® builds a context around the data.
• This enables advanced manipulations of data ranging from real time replica of sensor data to Machine Learning models, to 3D models.

Cognite Data Fusion® delivers contextualized data-as-a-service through a combination of machine learning, rules engines, and domain expertise.

Convert unstructured data into structured knowledge by liberating information trapped in documents, diagrams, images, videos, and more.