Know exactly which Oracle Fusion data you need — and run it in your own cloud.
Stop spending weeks guessing where Fusion keeps your data. Query it, find it and prove it in minutes with a free SQL editor — then turn it into a pipeline that runs in your AWS or Azure account.
What happens next: we reply within one business day with access. You sign in with your own Fusion user; queries run read-only through Oracle BI Publisher. Nothing to install.
FROM gl_ledgers
FETCH FIRST 100 ROWS ONLY
-- runs through BI Publisher, results in seconds
| NAME | LEDGER_CATEGORY_CODE | CURRENCY_CODE |
|---|---|---|
| US Primary Ledger | PRIMARY | USD |
| UK Primary Ledger | PRIMARY | GBP |
| US Secondary (IFRS) | SECONDARY | USD |
WHERE Status = 'ACTIVE'
LIMIT 100
-- the same extract your pipeline will deliver
| SUPPLIERID | SUPPLIERNAME | STATUS |
|---|---|---|
| 300000101134 | Acme Corp | ACTIVE |
| 300000203847 | Global Industries | ACTIVE |
? "bill rate"
-- 615K described columns across 4,545 PVOs
| PVO | COLUMN |
|---|---|
| BillingTransactionExtractPVO | PjbBillTransactionsBillRate |
| RevenueDistributionExtractPVO | RevenueDistributionPEOBillRate |
| InvoiceDistributionExtractPVO | InvoiceDistributionPEOBillRate |
SELECT ai.invoice_num, ai.invoice_amount, pv.vendor_name
FROM ap_invoices_all ai JOIN po_vendors pv
ON pv.vendor_id = ai.vendor_id
| R12 TABLE | FUSION PVO | MODULE |
|---|---|---|
| AP_INVOICES_ALL | InvoiceHeaderExtractPVO | Payables |
| PO_VENDORS | SupplierExtractPVO | Procurement |
One platform for the whole Fusion data lifecycle
Most tools start once you already know what to extract. FusionConvergeX starts earlier — and stays through production.
Fusion Discovery
- SQL editor: table SQL & PVO SQL
- Find any column across 4,545 PVOs
- PVO Selector, keys & watermarks
Migration Engineering
- R12 SQL → Fusion PVO mapping
- Gaps, reconciliation & star schemas
- Ready for Oracle's move beyond BICC
Data Engineering
- Extraction as code (YAML) + CI/CD
- Deployment kit for AWS & Azure (GCP preview)
- Incremental loads, monitoring, CLI
Product status: Available generally available Beta in use with customers, evolving Preview early access Roadmap planned
Built for the hard part of Oracle Fusion data
Generic ELT platforms can move data once the source is known. FusionConvergeX helps you decide what Fusion data to use, how legacy EBS data maps to it, how extraction should be modeled — and how it is deployed and operated in your enterprise platform.
We make Oracle Fusion understandable to it.
Find the right Fusion data — and prove it's there
A free SQL editor and a catalog of every Fusion PVO, so the question “which source has this?” takes minutes, not weeks. In the browser or on the desktop (macOS & Windows).
Table SQL in seconds
Query Fusion tables and views read-only through Oracle BI Publisher with your own credentials. Nothing to install.
Free AvailablePVO SQL
SELECT * FROM pvo:… runs the same extraction a pipeline will run — validate the data before you build anything.
Find any column
Search 615,000 described columns across 4,545 PVOs and 22 modules to find where Oracle keeps the field you need.
Free AvailablePVOs from R12 SQL
Paste an EBS R12 query and see which Fusion PVOs it needs, table by table.
Free BetaPVO Explorer Available
All 4,545 PVOs with described columns — primary keys and incremental watermark columns flagged.
SQL & base tables behind each PVO Available
See the Oracle SQL a PVO generates and the Fusion tables it reads; go from a table to its PVOs and back.
Schema versions & diff Available
Track PVO columns across Oracle releases and instances before a quarterly update breaks a load.
Flexfields per environment Available
Map DFF segments per client and instance so custom fields arrive with business names.
Start from the business question Roadmap
Describe the data you need — “project billing-rate overrides with employee, project, task and effective dates” — and get grounded recommendations: Fusion entities, sources, keys, watermarks and a draft YAML model, all from our Fusion metadata.
-- Is the data really here, and how much? SELECT COUNT(*) FROM pvo:BillingTransactionExtractPVO -- Which columns are actually populated? SELECT * FROM pvo:ExpenditureItemExtractPVO LIMIT 500 -- Does it tie out to the R12 report? SELECT ProjectBasePEOSegment1, ProjectBasePEOName FROM pvo:ProjectExtractPVO WHERE ProjectBasePEOSegment1 = '4588804' -- Will incremental work? Check the watermark SELECT MAX(ProjectBasePEOLastUpdateDate) FROM pvo:ProjectExtractPVO
- Source decisions backed by real row counts, not documentation
- No surprise empty columns in the warehouse
- Weeks of mapping workshops become an afternoon
Rebuild your EBS R12 reporting and data flows on Fusion
Years of R12 SQL already describe the data your business depends on. We turn that knowledge into Fusion sources, an extraction model and a target data model — so reporting continuity isn't a rewrite from scratch.
Analyze R12 SQL Beta
Bring existing queries and reports. We identify the R12 tables and columns they use (AP_INVOICES_ALL, PA_EXPENDITURE_ITEMS_ALL, …).
Map to Fusion Beta
Each R12 table and column is mapped to Fusion tables and the PVOs that expose them — with gaps flagged where Fusion has no equivalent.
Reconcile Beta
Run the PVO next to the R12 query it replaces and prove the numbers tie out before sign-off.
Model the target Available
Start from 489 Fusion subject-area star schemas to shape the warehouse your R12 reports are rebuilt on. Browse the library →
| EBS R12 table | Fusion PVO | Module | Notes |
|---|---|---|---|
| AP_INVOICES_ALL | InvoiceHeaderExtractPVO | Payables | Header columns map 1:1 for most reports |
| PO_VENDORS | SupplierExtractPVO | Procurement | Vendor → supplier model; sites split out |
| PA_PROJECTS_ALL | ProjectExtractPVO | Projects | segment1, name, status carried in the YAML |
| PA_EXPENDITURE_ITEMS_ALL | ExpenditureItemExtractPVO | Projects | Wide PVO — curated column list |
| GL_CODE_COMBINATIONS | CodeCombinationExtractPVO | General Ledger | Segments differ per chart of accounts |
| PA_EMP_BILL_RATE_OVERRIDES | No direct PVO | Projects | Gap flagged — alternate source proposed |
- Your existing R12 reports become the requirements document
- Gaps are found in week one, not in UAT
- Every Fusion column traces back to the R12 query that needed it
EBS R12 → Fusion Beta
Traceability from each Fusion column back to the R12 query that needed it — kept in the same YAML model that drives extraction, so migration decisions are reviewable and versioned.
BICC → Oracle Data Extraction Roadmap
Oracle now documents BICC as legacy and its RODS-based Data Extraction tool as the replacement. What to do next → Because your model is defined independently of the extraction engine, the plan is to let the same model run on either — preserving your downstream Databricks and Snowflake tables through the transition.
Define extraction as code. Run it in your cloud.
An intelligence and model layer above Oracle's extraction engines — delivering into the platform you already run.
Extraction engines are execution targets; your model, dependencies and downstream tables stay stable.
modules: - name: project_accounting groups: - group: projects_l1 depends_on: [enterprise_setup_l0] pvos: - pvo: FscmTopModelAM.PrjExtractAM.PjfBiccExtractAM.ProjectExtractPVO target_table: project primary_key: [ProjectBasePEOProjectId] watermark: [ProjectBasePEOLastUpdateDate] delete_mode: soft columns: [ProjectBasePEOProjectId, ProjectBasePEOSegment1, …] # from R12: PA_PROJECTS_ALL (segment1, name, project_status_code)
Extraction as code
- Every column choice is reviewed and versioned
- Jobs rebuilt exactly from the model — including default-off columns
- Dependencies live in the YAML (
depends_on) and drive load order - Incremental state tracked outside the extraction engine, with self-healing watermarks
- Same model promotes DEV → TEST → PROD
A true CI/CD pipeline architecture — for your Fusion data
The whole pipeline — sources, columns, keys, watermarks, dependencies, schedules and destinations — lives in git and ships like software. No console clicks, no configuration drift, every change reviewed and reversible.
- CommitAdd a source or column in YAML, open a pull request
- ValidateAutomated checks: schema, keys, watermarks, dependency order
- Deploy DEVExtraction jobs are built from the model and run
- PromoteSame YAML to TEST and PROD — only environment settings change
- Roll backRevert the commit; jobs are rebuilt exactly as before
GCP Preview
FusionConvergeX generates a deployment kit for AWS and Azure (GCP in preview): infrastructure templates plus pipeline code, wired to your YAML model. It covers roughly 90% of a production deployment; the rest is plain, readable code in your repository to adapt to your standards.
- Available Infrastructure-as-code — landing storage, serverless functions, scheduler, secrets, least-privilege roles
- Available Extraction & delivery code — job generation, watermark registry, dependency-ordered waves, multi-destination delivery
- Available Your YAML model · Beta CI/CD wiring
- Available Operator CLI —
fcxandbicc-pipelinefor jobs, loads, watermarks and recovery - Available Monitoring & runbook — alarms, delivery checks, row-count reports, day-2 operations
Incremental loads
An explicit time window on every extract, driven by your own watermark registry. Full reloads are one command.
Dependency-ordered waves
Reference data lands before the facts that depend on it — and load stays gentle on your network.
Verified delivery
Every run is checked end-to-end; any gap raises an alert and a per-source row-count report goes out after each run.
Rewind & recover
Reset a watermark, backfill a window or re-send a delivered run with one command — and roll back model changes by reverting the commit.
# build every extraction job from the YAML model $ fcx job create-from-yaml --all --model pvo_model.yaml # preview, then apply schedules $ bicc-pipeline schedule plan $ bicc-pipeline schedule apply # incremental load for a cadence, then check it $ fcx fire --cadence every_2h $ fcx rowcount ProjectExtractPVO --date 2026-09-26 # fix a watermark, re-send a delivered run $ fcx watermark seed ProjectExtractPVO "2026-09-01 00:00:00" $ bicc-pipeline republish
fcx job create-from-yamlfcx describe <pvo>bicc-pipeline schedule plan | applyfcx schedule statusfcx fire | backfillbicc-pipeline rewind | republishfcx rowcountbicc-pipeline status | historyYour Fusion data. Your cloud. Your architecture.
Production data pipelines run entirely in infrastructure you control; the discovery experience is hosted by us. Here is exactly what lives where.
| What | Where it lives |
|---|---|
| Business data (extracts) | Your cloud storage and data platform only |
| Production credentials | Your own vault / secret manager |
| Pipeline code & YAML model | Your git repository and cloud account |
| Production pipeline execution | Your cloud account only |
| SQL editor & catalog (discovery) | Hosted by FusionConvergeX |
| Fusion credentials used in the editor | Used only to run your read-only queries — we recommend a dedicated least-privilege discovery user, never a production service account |
Fusion to Azure, Databricks, AWS and Snowflake — every 30 minutes
Finance, projects, HR, procurement, supply chain and tax data flows from Oracle Fusion Cloud into customers' data lakes, Databricks and Snowflake on a 30-minute incremental cadence — dependency-ordered from the YAML model, fanned out to several environments at once, and verified after every run.
Built by Oracle Fusion data engineers
FusionConvergeX is built by practitioners who run these pipelines in production — the same engine, YAML model and runbooks we sell. Enterprise references available on request.
Where FusionConvergeX fits
A comparison of primary focus by category — not a claim about what any product can do with customization.
| Generic ELT / connectors | Oracle-managed analytics | FusionConvergeX | |
|---|---|---|---|
| Deciding what Fusion data to use | Assumes you know | Prebuilt subject areas | Discovery, PVO SQL, column search |
| EBS R12 → Fusion mapping | No | No | R12 SQL → PVOs, reconciliation |
| Extraction model as code (git, CI/CD) | Connector config | Oracle lifecycle | YAML model |
| Runs in your own cloud | Usually SaaS | Oracle stack | AWS, Azure, GCP |
| Keeps your Databricks / Snowflake architecture | Yes | Oracle lakehouse | Yes |
| Pricing basis | Rows / volume | Oracle subscription | Flat, by environment |
Move business transactions between applications.
Engineer Oracle Fusion data into your enterprise data platform.
Practical answers from production Fusion pipelines
BICC is legacy. What should Fusion data teams do next?
What Oracle's Data Extraction tool changes — and how to prepare without re-platforming twice.
Incremental loadsWhat actually controls a BICC incremental extract
Why rows keep coming back — and why a “full load” can return 43 rows instead of 225,903.
TroubleshootingORA-00918 on an extract? Curate the columns
How wide PVOs break, and the column-list fix.
TroubleshootingColumns missing from your extract? Check isPopulate
Default-off columns that silently disappear.
ProductionFusion to Azure or Databricks: a production checklist
Ordering, network load, deletes and verified delivery.
Start free. Scale to production.
Discovery is free. Production packages are priced by environment and scope — never per row.
Free — no credit card
- SQL editor: table & PVO SQL
- Column search across 4,545 PVOs
- R12 SQL → PVO lookup
- Community guides
Paid — when you go to production
- Deployment kit generated for your cloud
- YAML model, CI/CD wiring & environment promotion
- Incremental orchestration, monitoring & row-count reports
- Support, security review & onboarding
- SQL editor: table & PVO SQL
- Column search & PVO Explorer
- R12 SQL → PVO lookup
- Web & desktop
- Everything in Explorer
- Saved YAML models & git
- R12 mapping & reconciliation
- Non-production deployments
- Everything in Team
- Deployment kit: AWS, Azure (GCP preview)
- Incremental orchestration
- Monitoring & delivery checks
- Support
- Multi-environment governance
- Security review support
- Private deployment
- Priority support & SLA
Questions
Is FusionConvergeX a SQL editor or a pipeline tool?
Both, and more: it covers the Fusion data lifecycle from discovery (SQL editor, PVO catalog) through R12 → Fusion migration engineering to data engineering (extraction as code, deployment into your cloud, monitoring). The SQL editor is free to start.
What's the difference between table SQL and PVO SQL?
Table SQL runs against Fusion tables and views through BI Publisher and returns in seconds. PVO SQL (FROM pvo:…) runs an extraction of a Public View Object — the same one your pipeline loads — so you can validate exactly what will be delivered.
What runs on your side, and what runs in ours?
Production data pipelines run entirely in your cloud: the deployment kit, production extraction, production credentials, business data and pipeline execution all stay in infrastructure you control. FusionConvergeX hosts the design and discovery experience — the SQL editor and catalog. Use a dedicated, least-privilege, read-only Fusion user for discovery; production credentials never leave your cloud.
Oracle is replacing BICC with the Data Extraction tool. What does that mean for us?
Your YAML model describes sources, columns, keys and dependencies independently of the extraction engine. BICC is supported today; support for Oracle's RODS-based Data Extraction tool is on our roadmap, with the goal of keeping your downstream tables unchanged through the transition.
How is this different from a data connector like Fivetran?
Connectors solve data movement once you know the source. FusionConvergeX solves the Oracle Fusion engineering problem around it: deciding what to extract, mapping legacy EBS data to Fusion, modeling the extraction, deploying it into your architecture and operating it. The two can work together — FusionConvergeX can define and validate what a downstream tool moves.
Is this an integration platform like Boomi, MuleSoft or OIC?
No. Integration platforms move business transactions between applications. FusionConvergeX engineers Oracle Fusion data into your enterprise data platform for analytics, reporting and AI.
Do I need Oracle admin access?
No. For current BICC-based extraction, a least-privilege Fusion service account with the required BICC and BI Publisher permissions is sufficient — no Fusion database login. Permissions for Oracle Data Extraction (RODS) will be documented as support becomes available.
Which clouds and platforms do you deliver to?
AWS and Azure today, with GCP in preview — and the platforms built on them, including Databricks, Snowflake and BigQuery. One pipeline can deliver to several environments at once.
Make Oracle Fusion understandable to your data platform.
Start with the free SQL editor. When you're ready for production, we'll help you deploy.