Optimizing data models for AI
Learn how to model data to support natural language queries and enable Atlas AI agents across domains and workflows.
Designing scalable data models
Learn best practices for designing scalable data models in CDF, including layered architecture, design principles, and performance optimization.
Building an asset hierarchy
Build an asset hierarchy with the Cognite core data model and populate it with transformations.
Extending the core data model
Create custom data models by extending the core data model using GraphQL data modeling language.
Integrate with files
Connect files to your data model instances using the Cognite core data model.
Integrate with time series
Link time series data to your data model instances for operational insights.
Performance considerations
Understand key factors that impact performance when ingesting and querying data.
Debug query performance
Use debug notices to analyze and optimize your data model queries.
Manage in CI/CD
Deploy and manage your data models using continuous integration and deployment workflows.
Clean up nodes without data
Delete nodes that don’t have associated container data using a Python script.