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oracle-samples/oracle-aidp-samples

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Oracle AI Data Platform Workbench Samples

Обзор

This repository contains a curated collection of sample notebooks demonstrating how to build data pipelines, run machine learning workloads, and integrate AI capabilities using — a unified, governed workspace for data engineering, ML, and AI development powered by Apache Spark. Oracle AI Data Platform Workbench is 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. Foundational examples to help you get up and running on AIDP Workbench. The native Iceberg sample uses an existing AIDP Standard catalog. The Hadoop catalog sample under Data Engineering registers a separate Spark catalog on OCI Object Storage. Delta UniForm samples create Delta tables that publish Iceberg-compatible metadata.

README

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Oracle AI Data Platform Workbench Samples

This repository contains a curated collection of sample notebooks demonstrating how to build data pipelines, run machine learning workloads, and integrate AI capabilities using Oracle AI Data Platform (AIDP) Workbench — a unified, governed workspace for data engineering, ML, and AI development powered by Apache Spark.

What is Oracle AI Data Platform Workbench?

Oracle AI Data Platform Workbench is 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.

Learn more about AIDP Workbench →


Repository Structure

oracle-aidp-samples/
├── getting-started/          # Foundational notebooks for new users
│   ├── Delta_Lake/           # Delta Lake feature walkthroughs
│   └── migration/            # Migrating workloads to AIDP
├── data-engineering/
│   ├── ingestion/            # Connectors and data loading patterns
│   │   └── landing-zone-auto-ingestion/
│   ├── lineage/              # Reading and visualizing AIDP data lineage
│   └── transformation/       # Pipeline architectures and table formats
│       ├── delta-clone-metadata/
│       ├── liquid-clustering/
│       ├── medallion-lake/
│       ├── scd/
│       └── streaming/
├── ai/
│   ├── agent-hub/            # Agent Hub code-first agent samples
│   │   └── agent-samples/
│   ├── agent-flows/          # Agent orchestration and scheduling
│   ├── ml-datascience/       # ML, LLM, and AI service integrations
│   └── skills/               # Agent Skills (SKILL.md packages) by product domain
│       └── analytics/        # Oracle Analytics skills
└── shared-utils/             # Reusable utilities and data generators

Sample Catalog

Getting Started

Foundational examples to help you get up and running on AIDP Workbench.

Notebook Description
Access ALH Data Write and query data in Oracle Autonomous AI Lakehouse (ALH) using PySpark insertInto and SQL INSERT statements with external catalogs.
Access Object Storage Data Read and write data from OCI Object Storage using direct access, external volumes, and external tables.
Analyse Data Using PySpark PySpark fundamentals: catalog and schema setup, table creation, data insertion, schema exploration, and matplotlib visualizations.
Analyse Data Using SQL Core SQL operations on AIDP including DataFrame creation, transformations, aggregations, and simple visualizations.
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Установка

npx skillfish add oracle-samples/oracle-aidp-samples
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