Canonical Schema

What is a Canonical Schema?

Canonical schema is a data model that translates between different data formats. This approach usually is used to abstract away the underlying complexities of specific implementation formats to focus on a common, high-level format. After mappings are created from each implementation to the common data model, applications based on that model are insulated from changes or variations in the underlying data sources, simplifying application development and maintenance.


Why is a Canonical Schema Important?

A canonical schema provides the basis for a model-driven architecture, which enterprises can use to create a common architecture for developing scalable, integrated applications spanning multiple functions and processes within their organization. Instead of having to maintain every single connection between every data source (D) and application (A) – potentially a D times A number of connections – developers can use the common data model to reduce the number of connections to D plus A. Adding new data sources and applications requires much less effort and time using the common data model.


How Enables Organizations to Leverage Canonical Schemas provides a complete, end-to-end, scalable platform based on a model-driven architecture – the C3 AI® Suite – that takes full advantage of the benefits of a canonical schema to enable designing, developing, deploying, and operating enterprise AI applications at industrial scale. With the C3 AI Suite, organizations can accelerate development of these applications on cloud platforms such as AWS and Azure 25-fold and deploy them in one-tenth the time of other approaches. Because of’s revolutionary model-driven architecture, applications developed with the C3 AI Suite can run on any cloud with little or no change to the application code. also delivers a portfolio of prebuilt, SaaS enterprise AI applications for a growing number of use cases such as predictive maintenance, inventory optimization, fraud detection, and anti-money laundering. Some of the world’s largest organizations – including Shell, the US Department of Defense, Enel, and Koch Industries – use technology to drive digital transformation initiatives that significantly reduce costs, increase asset availability and reliability, improve human safety, and enhance customer satisfaction. These applications run out of the box on the leading cloud platforms. A application can be configured to take advantage of microservices available from different cloud providers – for example, AWS’s image recognition can be combined with Google’s natural language processing in the same application.