Glossary

Data Integration Design

What is Data Integration Design?

Data integration design, a critical part of the product specification for any enterprise AI application, identifies design parameters for source data formats, frequency of updates, historical and incremental data volumes, transformation methods, and mappings from conceptual to logical to physical data models.

 

Why is Data Integration Design Important?

Data integration design drives the target end user experience, so its specification must be comprehensive for the given use cases while allowing extensibility to cover new use cases and data sources for future opportunities.

 

How C3.ai Enables Organizations to Use Data Integration Design

The C3 AI® Suite is a complete, end-to-end platform for designing, developing, deploying, and operating enterprise AI applications at industrial scale. C3 AI Data Studio is a set of visual tools to ingest disparate internal, external, and sensor data into a unified, federated image, enabling the design and exploration of the sources, structure, and content that result from the C3 AI Data Model. Its data management and data explorer tools set up and provide access to integration pipelines and allow visual exploration and transformations to ensure data is ready for analysis.

C3.ai has published its application development methodology to define the best practices that enterprises should adopt to gain the most value from their AI platform [link: https://c3ai.gitbook.io/c3-program-methodology/-LikM5DSbLoN9YFkm0WD/v/master/specify/integration-architecture-specification]

C3.ai has created standard data models for a variety of industries and use cases, and offers the services of domain experts to assist customer development through establishing a Center of Excellence.