AI Data Platform Workbench
A unified, governed workspace for building, managing, and deploying AI and data-driven solutions. It brings together notebooks, agent development, orchestration, and catalog management in a single collaborative platform—empowering teams to explore data, fine-tune models, and operationalize AI with trust and speed.
Oracle AI Data Platform’daki yenilikler neler?
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Product tour—AI Data Platform Workbench
Data control
AI Data Platform embeds strong controls with fine-grained permissions, helping to improve more secure, compliant access to catalogs, assets, and notebooks while maintaining trust, consistency, and auditability.
Medallion architecture
AI Data Platform’s governed medallion architecture, including raw bronze, refined silver, and trusted gold, helps ensure consistency, quality, and AI readiness at every stage, turning diverse data into reliable insights for any use case.
Developer experience
Interactive notebooks integrated with the catalog enable developers to code across languages, explore data from raw to curated, and seamlessly collaborate with engineers, scientists, and business users on trusted data sets.
Orchestration
AI Data Platform streamlines end-to-end workflows with visual orchestration, automation, and scheduling, making it easy to design, monitor, and troubleshoot pipelines while enabling data quality, governance, and collaborative transparency across teams.
AI Data Platform Workbench features
Unified lakehouse for all data and AI assets
Centralized master catalog
Discover and organize all data and AI assets across structured, semi-structured, and unstructured sources in a unified catalog.
Support for medallion architecture
Natively manage bronze, silver, and gold data layers with lineage and quality tracking to support trusted AI and analytics.
Multi-format data support
Seamlessly ingest and analyze data from files, databases, documents, images, and more—all within one platform.
Built-in governance and metadata management
Apply access policies, tagging, and audit trails across all data and AI artifacts to enable compliance and reuse.
End-to-end development with Spark and Autonomous AI Database
Flexible compute options
Run data pipelines and ML workloads on Apache Spark and/or Oracle Autonomous AI Database.
Unified workflow orchestration
Build and orchestrate batch and streaming jobs with versioning, dependency tracking, and integration through APIs.
Integrated data science and engineering
Combine data transformation, feature engineering, and model training into unified pipelines without moving data between tools.
Enterprise integration across Oracle and third-party ecosystems
Open ecosystem and standards support
Direct connectivity to external systems using REST, JDBC, Kafka, and open metadata standards for cross-platform AI integration.
Native connectivity to Oracle Applications
Direct access to operational data from Fusion Applications and Fusion Analytics.
Deep integration with Oracle technologies
Orchestrate data and AI with Autonomous AI Database, Oracle GoldenGate, and Oracle Analytics Cloud.
