Skip to main content

aidp-fusion-pipeline

Productized Fusion → Oracle AI Data Platform pipeline with curated BICC extracts (GL/AR/AP/PO/Suppliers/Items), bronze/silver/gold medallion in Delta, conformed dimensions (account/calendar/org/supplier/item), gold marts (AR-Aging/AP-Aging/GL-Balance/PO-Backlog/Supplier-Spend), and MCP-native OAC workbook authoring. Use when the user wants to load Fusion ERP/HCM/SCM data into AIDP, build a CFO dashboard from Fusion, set up a Fusion-backed lakehouse, create OAC datasets/workbooks over AIDP gold, set up OAC MCP for operator authoring or natural-language Fusion analytics in Claude/Cline/Copilot, run BICC extracts incrementally, productize the Oracle blog "Bring Fusion Data into AIDP Workbench Using BICC", or extract Fusion via the saas-batch REST API. Triggers — "load Fusion into AIDP", "set up Fusion bronze layer", "build CFO dashboard from Fusion", "create OAC workbook from Fusion", "run BICC extract", "Fusion AIDP medallion", "saas-batch Fusion extract".

Ir para a instalação

Informações da origem

Repositório
oracle-samples/oracle-aidp-samples
Última atividade na origem
2 de agosto de 2026 às 08:34
Idioma detectado do SKILL.md
inglês
Estrelas
46
Forks
30

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Revise os arquivos de origem

Leia o SKILL.md e os arquivos complementares exibidos pelo SkillsMP antes de decidir se vai instalar.

Exibindo SKILL.md

SKILL.md
Instruções da origem · Visualização somente leitura
name
aidp-fusion-pipeline
description
Productized Fusion → Oracle AI Data Platform pipeline with curated BICC extracts (GL/AR/AP/PO/Suppliers/Items), bronze/silver/gold medallion in Delta, conformed dimensions (account/calendar/org/supplier/item), gold marts (AR-Aging/AP-Aging/GL-Balance/PO-Backlog/Supplier-Spend), and MCP-native OAC workbook authoring. Use when the user wants to load Fusion ERP/HCM/SCM data into AIDP, build a CFO dashboard from Fusion, set up a Fusion-backed lakehouse, create OAC datasets/workbooks over AIDP gold, set up OAC MCP for operator authoring or natural-language Fusion analytics in Claude/Cline/Copilot, run BICC extracts incrementally, productize the Oracle blog "Bring Fusion Data into AIDP Workbench Using BICC", or extract Fusion via the saas-batch REST API. Triggers — "load Fusion into AIDP", "set up Fusion bronze layer", "build CFO dashboard from Fusion", "create OAC workbook from Fusion", "run BICC extract", "Fusion AIDP medallion", "saas-batch Fusion extract".
allowed-tools
Read, Write, Edit, Bash, Glob, Grep
# `aidp-fusion-pipeline` — Fusion ERP/HCM/SCM → AIDP, batteries included Productizes the official Oracle blog [Bring Fusion Data into Oracle AI Data Platform Workbench Using BICC](https://blogs.oracle.com/ai-data-platform/bring-fusion-data-into-oracle-ai-data-platform-workbench-using-bicc) plus the ateam companion [How to Extract Fusion Data using Oracle AI Data Platform](https://www.ateam-oracle.com/how-to-extract-fusion-data-using-oracle-ai-data-platform). The current path is: configure → connect OAC MCP → bootstrap → seed AIDP gold → advise the OAC dataset → use `oac-dataset-setup` for the governed manual OAC connection/dataset checkpoint → author the workbook via OAC MCP. When a run, bootstrap, validation, dashboard, or workbook flow reports an `AIDPF-*` code, start with [`aidpf-error-triage`](../aidpf-error-triage/SKILL.md). It is read-only and routes the failure to the recovery skill that owns it. ## When to use - User wants Fusion data in AIDP and asks "where do I start" - User has BICC privileges and wants curated bronze/silver/gold layers without writing the pipeline - User is preparing a CFO/analytics demo and needs OAC dashboards on Fusion data - User wants to use [OAC MCP (Preview)](https://docs.oracle.com/en/cloud/paas/analytics-cloud/acsdv/access-oracle-analytics-cloud-mcp-server-preview.html) to chat with Fusion data via Claude/Cline/Copilot ## When NOT to use - For a single one-off PVO read → use [`aidp-fusion-bicc`](../../../oracle-ai-data-platform-workbench-spark-connectors/skills/aidp-fusion-bicc/SKILL.md) (sibling plugin, smaller scope). - For Fusion REST queries with <50k rows → [`aidp-fusion-rest`](../../../oracle-ai-data-platform-workbench-spark-connectors/skills/aidp-fusion-rest/SKILL.md). - For EPM Cloud Planning data slices → [`aidp-epm-cloud`](../../../oracle-ai-data-platform-workbench-spark-connectors/skills/aidp-epm-cloud/SKILL.md). - For Essbase MDX → [`aidp-essbase`](../../../oracle-ai-data-platform-workbench-spark-connectors/skills/aidp-essbase/SKILL.md). ## Positioning This bundle is **additive to and complementary with** Oracle's managed Fusion data offerings. It productizes Option 1 of pdf1's three-option architecture (BICC into AIDP for "Custom AI and ML, raw data access, data engineering"). Never positioned as a replacement for FDI, OAC, OTBI, BIP, or Data Transforms. ## What you get Mirrors pdf1 §"What Can You Do Once the Data is in Oracle AI Data Platform": 1. **Custom ML/AI training** on operational ERP/HCM/SCM data (PySpark + Python in AIDP notebooks) 2. **Cross-source enrichment** — join Fusion data with non-Fusion sources via the `aidataplatform` connector family 3. **Medallion architecture** — bronze (raw audit) → silver (typed + dim-joined) → gold (business marts) in Delta 4. **GenAI agent grounding** — `ai_generate("which suppliers had >$1M Q1 spend?")` against gold marts via OCI Generative AI 5. **BI & reporting via JDBC** — OAC, Tableau, Power BI consume the gold layer 6. **Delta Sharing** (v3 roadmap) — share curated datasets with other teams or external partners ## Quickstart > **Recommended route:** install the Claude Code plugin, open Claude Code from a > clean customer bundle directory such as `Workspace/demo-fusion-cfo/`, then > invoke [`aidp-fusion-autopilot`](../aidp-fusion-autopilot/SKILL.md) with the > dashboard goal. Autopilot installs/uses the bundled CLI if needed, scaffolds > customer files, and conducts the whole chain (configure → OAC MCP setup → > bootstrap → seed → advise → dataset → workbook → optional MCP chat), pausing > only for real decisions. Keep the customer directory separate from the plugin > source. The manual quickstart below is the step-by-step path autopilot > automates. 1. **Install the CLI** on your laptop: ```bash pip install -e /path/to/oracle-ai-data-platform-fusion-autopilot ``` 2. **Scaffold a bundle in your repo**: ```bash aidp-fusion-autopilot init ``` Edits `bundle.yaml` and `aidp.config.yaml` to match your environment (Fusion pod URL, AIDP workspace, OAC URL, OCI Vault refs for credentials). 3. **Connect operator OAC MCP early**: ```bash env -u OAC_URL -u OAC_MCP_USER -u OAC_MCP_PASSWORD -u OAC_ADMIN_USER -u OAC_ADMIN_PASSWORD \ aidp-fusion-autopilot dashboard mcp-setup \ --connector-js <path to oac-mcp-connect.js> ``` Run from the customer project directory. The `env -u ...` wrapper lets the local `.env` provide the OAC values instead of any global shell profile. Restart/reconnect Claude Code after this. Autopilot and workbook-authoring need OAC MCP for `search_catalog`, `describe_data`, and `save_catalog_content`. If setup happens mid-journey, autopilot writes `.aidp/autopilot/resume.md`; resume with: "Resume the Fusion dashboard workflow from .aidp/autopilot/resume.md." 4. **Probe prerequisites and pin tenant variation**: ```bash aidp-fusion-autopilot bootstrap --check-iam ``` Prefer to drive this conversationally? Use [`aidp-fusion-bootstrap`](../aidp-fusion-bootstrap/SKILL.md). It confirms BICC role, BICC External Storage profile (set in BICC console), AIDP catalog, IAM policies, Vault access, and routes unresolved variation to `medallion-author`. 5. **Run the orchestrator**: ```bash aidp-fusion-autopilot run --mode seed # first-time full extract aidp-fusion-autopilot run --mode incremental # daily delta ``` Prefer to drive this conversationally? The [`aidp-fusion-seed`](../aidp-fusion-seed/SKILL.md) skill turns "seed", "seed supplier_spend", "seed just bronze", or "resume the seed" into the correct guarded `run --mode seed` invocation — it parses the scope, auto-satisfies preconditions (validate / `/aidp-fusion-bootstrap` / cluster), and **fail-closed-confirms** before overwriting populated silver/gold marts. If the run reports an `AIDPF-*` code, use [`aidpf-error-triage`](../aidpf-error-triage/SKILL.md) before choosing a recovery path. 6. **Build dashboards (MCP-native — the current path).** Ask [`oac-dataset-advisor`](../oac-dataset-advisor/SKILL.md) what OAC dataset your goal needs (grounded in the **live** AIDP gold layer), use [`oac-dataset-setup`](../oac-dataset-setup/SKILL.md) to guide the manual AIDP connection/dataset step and verify it through MCP, then have [`workbook-authoring`](../workbook-authoring/SKILL.md) generate the visualization(s) and write them via the OAC MCP `save_catalog_content` tool. If the gold layer can't serve the goal, [`mart-author`](../mart-author/SKILL.md) authors a new mart (then `use-pack` + seed). *Legacy alternative:* the `.bar` snapshot `dashboard install` flow (snapshot register + restore via OAC REST) still ships — see `docs/oac_rest_api_setup.md` — but the MCP-native family above supersedes it for authoring. 7. **End users chat with the data** via OAC MCP. Set up the connector for Claude Code (non-interactive **basic auth**, the path that actually works in a terminal client): ```bash env -u OAC_URL -u OAC_MCP_USER -u OAC_MCP_PASSWORD -u OAC_ADMIN_USER -u OAC_ADMIN_PASSWORD \ aidp-fusion-autopilot dashboard mcp-setup \ --connector-js <path to oac-mcp-connect.js> ``` Then ask "what's our AR aging?" and watch MCP call `search_catalog` → `describe_data` → `execute_logical_sql` against `fusion_catalog.gold.*`. **Scope the OAC user to least privilege** — the v1.4 connector exposes catalog write/delete/ACL tools governed by that user's grants. ## Key gotchas - **BICC role required** — Fusion user must hold `BIA_ADMINISTRATOR_DUTY` *or* `ORA_ASM_APPLICATION_IMPLEMENTATION_ADMIN_ABSTRACT`. Without it, `/biacm/api/v[12]/*` endpoints 302-redirect to IDCS. Bootstrap probes for this. - **BICC External Storage profile** — must be configured **once in the BICC console** (admin task: BICC Console → Configure External Storage → OCI Object Storage Connection tab → bucket name + namespace + region + OCI username + auth token → Test Connection → Save). The `fusion.external.storage` Spark option references this BICC profile name. **There is no parallel AIDP-side registration.** Bundle does not provision the BICC profile; bootstrap verifies it exists. - **First extract is slow** — BICC builds a full snapshot on first call; subsequent runs use `fusion.initial.extract-date` for incremental. - **499 row/page hard cap on Fusion REST** (per MOS Doc ID 2429019.1) — bundle's REST fallback enforces this; anything >5k rows must use BICC. - **OAC MCP (v1.4) is NOT read-only** — it exposes catalog **write** tools too. The bundle authors workbooks via `save_catalog_content` (live-verified 2026-06-15: created `gold_balance_2viz` on a real OAC). It still **cannot create datasets** (no create-dataset tool — dataset modeling is an OAC UI step), and the write/delete/ACL tools run with the connecting user's grants → use a least-privilege MCP user. (Supersedes the earlier "MCP is read-only" note.) - **`POST /catalog/connections` REST validator does not bless AIDP `idljdbc`** — Oracle's validator falls through to generic Oracle DB schemas requiring `serviceName`/`password`/`connectionString`. The realistic flow is therefore: customer creates the connection via OAC UI once (using the 6-key JSON written by `--print-only`). Legacy `dashboard install` can re-use that connection via the precheck on subsequent `.bar` snapshot deployments. - **Snapshot BAR URI shape is `file:///<folder>/<name>.bar`** — NOT `oci://...`, NOT bare object name, NOT the OCI Object Storage HTTPS URL. - **OAC catalog browse needs `search=*`** — `GET /catalog?type=connections` (no search) returns a single-element TypeInfo header (`[{"type":"connections"}]`), NOT the actual list. Bundle's `list_connections` defaults `search="*"` so the precheck works. - **Use ExtractPVOs for bulk, NOT OTBI reporting PVOs** — pdf1 Pro Tip; bundle's catalog refuses OTBI PVOs with a clear warning. ## References - Plan: `C:\Users\anuma\.claude\plans\oracle-ai-data-platform-fusion-autopilot.md` - Sibling plugin (single-PVO connector): [`oracle-ai-data-platform-workbench-spark-connectors`](../../../oracle-ai-data-platform-workbench-spark-connectors/) - Official Oracle BICC blog: https://blogs.oracle.com/ai-data-platform/bring-fusion-data-into-oracle-ai-data-platform-workbench-using-bicc - Ateam blog (saas-batch path): https://www.ateam-oracle.com/how-to-extract-fusion-data-using-oracle-ai-data-platform - Official sample notebook: [`oracle-aidp-samples/data-engineering/ingestion/Read_Only_Ingestion_Connectors.ipynb`](../../../../data-engineering/ingestion/Read_Only_Ingestion_Connectors.ipynb) - OAC MCP Preview docs: https://docs.oracle.com/en/cloud/paas/analytics-cloud/acsdv/access-oracle-analytics-cloud-mcp-server-preview.html
Ver no GitHub