Data Integration
The C3 AI Suite helps integrate, federate, and unify all disparate enterprise and external data into a logical data image. Developers and data engineers can use metadata transformation expressions to combine data entities, leverage AI-based data reconciliation capabilities, maintain data lineage, and enforce data governance. The C3 AI Suite provides flexibility in making fine-tuned decisions to ingest and persist data in the C3 AI Suite-mediated data stores for faster performance or use a virtual data image to reuse existing data lake investments.
One Platform for Data Integration
- Integrate all enterprise and external data on the C3 AI Suite’s flexible, scalable, and reliable model-driven architecture.
- Ingest data from a broad range of internal and external data stores.
- Persist data into relational, key value, or file storage systems.
- Ingest data in real-time, in batches, from continuous streams, or through event-triggered mechanisms.
- Create reusable multi-step transformations between source and target data stores.
- Visualize and manage transformations library in the low-code / no-code C3 AI Data Studio environment.
Unified Federated Data Image
The C3 AI Suite enables building, navigating, and exploring a unified federated image of data entities across persistence technologies.
- Unify your enterprise and external data on a common federated data image leveraging the C3 AI Suite’s model driven architecture.
- Choose from pre-built enterprise object models to unify your data or custom build your own data model from scratch.
- Explore, navigate, and visualize your data model using C3.ai Data Studio
Virtual Data Lake
The C3 AI Suite enables data virtualization for organizations to leverage existing investments in data stores and data lakes by unifying all data into a unified virtual data image, eliminating the need to duplicate data.
- Present a unified virtual layer of data from disparate sources and provide to users as if from a single source
- Create, update, or delete data for any object
- Invoke analytics to analyze and explore data on the C3 AI Suite
- Infer and expose metadata from source schemas
Data Connectors
The C3 AI Suite provides over 25 pre-built connectors to access cloud and on-premise data sources. Developers and data engineers can directly utilize the connectors to integrate data on the C3 AI Suite without developing any custom integrations.
- Databases and big-data stores including Snowflake, Impala, HBase, Postgres, CosmosDB, MongoDB, Oracle, AWS RedShift, SQL Server
- Cloud applications including Salesforce, HubSpot
- Queue-based systems including Apache Kafka, Azure Event HUbs, Azure Topics, AWS Kinesis, AWS SQL
- File systems including AWS S3, Azure Data Lake Store gen2, Azure Blob, HDFS, local file system
Enterprise Object Models
C3.ai offers a variety of pre-built object models that can accelerate development of enterprise AI applications
- Industry Object Models comprise predefined integration canonicals, data models, and time-series for industries such as oil and gas, utilities, financial services, aerospace and defense, and manufacturing.
- Functional Packages comprise supervised & unsupervised ML models, an ML interpretability framework, and user interface tooling to address high-value use cases.
- ML Packages contain methods for predictive analytics such as anomaly detection, NLP, object detection, and forecasting .
Companies can also choose to extend the pre-built object models to reflect their unique business or develop custom new object models
