Migration route

    SAP R/3→Oracle Fusion

    SAP R/3 to Oracle Fusion Data Migration

    Migrate financials, master data, historical data from SAP R/3 to Oracle Fusion Cloud Applications using a controlled process for extraction, mapping, transformation, validation, loading and reconciliation.

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    Migration overview

    SAP R/3 to Oracle Fusion is legacy modernisation rather than an ERP swap. An estate still on R/3 has usually been running it for a very long time, which means decades of configuration, custom development and data whose original owners have moved on.

    The commercial driver is normally the cost and risk of keeping an out-of-support platform alive. That makes the archive question central: the programme succeeds by moving what the new ERP needs and preserving the rest somewhere it can still be read.

    Typical data scope

    Scope is agreed in discovery. On this route it usually covers:

    Financials

    Domain in scope for a typical SAP R/3 to Oracle Fusion programme.

    Master data

    Domain in scope for a typical SAP R/3 to Oracle Fusion programme.

    Historical data

    Domain in scope for a typical SAP R/3 to Oracle Fusion programme.

    Migration architecture

    One controlled pipeline, run as repeatable cycles.

    SAP R/3→DataMove→Transformation & validation→Oracle Fusion→DataVault reconciliation→DataLens

    Extracting from SAP R/3

    What the source platform makes available, and the constraints that shape the extraction design.

    Non-Unicode codepagesMany R/3 installations were never converted to Unicode. Text sits under a legacy codepage, so extended characters need explicit conversion on extract. Skip it and names and addresses arrive corrupted — while every record count still reconciles, because the row is there and only its contents are wrong.
    Classic G/L rather than New G/LR/3 typically runs classic General Ledger: no document splitting, totals maintained separately from line items, segment reporting through special ledgers. The financial model being read is not the one a modern target expects.
    MANDT — client partitioningAs in ECC, application tables are client-dependent and an unconstrained extract blends clients.
    ADK archive filesData already archived out of R/3 lives in ADK archive files, not the database. If that history is in scope it must be read through the archive layer — a common late discovery on legacy estates.
    Custom Z-tables and modificationsA long-running R/3 estate accumulates custom tables and modified standard objects holding data the business depends on. Profiling finds them; a standard object list does not.
    Older extraction toolchainR/3 predates the modern integration surface. Extraction generally means ABAP extract programs or database-level reads rather than OData services.

    Source-to-target mapping

    A mapping workbook carries every field in scope from its SAP R/3 source through its transformation rule to the Oracle Fusion target object and field. It is reviewed and approved with the business before the production migration, and applied identically in every cycle so a decision made once is not re-made under cutover pressure.

    Transformation challenges on this route

    The differences between SAP R/3 and Oracle Fusion that create most of the work.

    Non-Unicode character conversion

    Many R/3 installations were never converted to Unicode. Extended characters need explicit codepage conversion on extract, and the failure is invisible to count-based reconciliation — every row is present and only its contents are corrupted.

    Classic G/L reconciliation

    Classic General Ledger keeps totals separately from line items and has no document splitting, so the reconciliation design follows the source's actual accounting model rather than assuming New G/L behaviour.

    Archived data outside the database

    History already archived through SAP's archiving lives in ADK files that ordinary SQL extraction cannot see. If it is in scope, it is read through the archive layer.

    Undocumented customisation

    Custom tables and modified standard objects hold data the business relies on and appear in no standard object list.

    Fusion's structure has to be built first

    Chart of accounts, ledgers, legal entities and business units exist before any R/3 transactional data can be positioned.

    How Oracle Fusion accepts the data

    Load order is part of the design, not an implementation detail.

    1. 1Pick the load mechanism per objectFBDI for Financials, Procurement and SCM; HDL for HCM and Payroll; ADFdi spreadsheets for small corrective loads; REST and SOAP for integration rather than bulk migration. The choice fixes the file format, so it is made before transformation is built.
    2. 2Build to the Oracle template exactlyFBDI templates are column-position-sensitive CSV. A shifted column does not raise a useful error — it writes a valid-looking wrong value, so generated output is validated against the template rather than inspected by eye.
    3. 3Load the enterprise structure firstChart of accounts, ledgers, legal entities, business units, cost centres and their value sets. Transactional data referencing a structure that does not exist yet fails at import.
    4. 4Load master dataSuppliers, customers and items become the reference points transactional records resolve against, carrying a cross-reference to the legacy key where it retains audit value.
    5. 5Upload and invoke the importFiles are zipped and uploaded to UCM; the Load Interface File for Import job stages them into interface tables; the object's import process promotes them into base tables.
    6. 6Work the interface-table rejectionsA row can pass the file load and still fail the import on a referential or business-rule check. Rejections are categorised, fixed in the transformation rules and reprocessed.
    7. 7Load transactional and historical dataBalances, open items and history, in the order the target's own validations require.

    Two stages, two failure modes. Source-to-file reconciliation proves the transformation was right; file-to-target reconciliation proves Oracle accepted it. Check only the first and a migration reports success while rows sit rejected in an interface table.

    Validation and reconciliation

    Validation before load

    Mandatory fields, referential integrity, format checks, business-rule validation and duplicate detection run on the prepared data, so problems surface as reportable exceptions rather than as failed loads in Oracle Fusion.

    Reconciliation after load

    Source counts, transformed counts, rejected records and target counts, with control totals where the data supports them. Every discrepancy is categorised so the migration is approved on evidence rather than assertion.

    Migration cycles

    The pipeline is run end to end more than once before anything touches production. A typical structure is a first rehearsal that surfaces the bulk of mapping and data-quality corrections, a second that applies them and demonstrates production readiness, and the production cutover itself. How many cycles a programme needs depends on data quality and scope, which is established during discovery.

    1. 1Mock / PPR 1First full extract, transform, load, reconcile and exception analysis. Expect the largest correction list here.
    2. 2Mock / PPR 2Corrections applied, re-extract, re-run. Intended to closely replicate the production migration.
    3. 3Production cutoverFinal extract, data freeze, load, reconciliation, business validation and sign-off.

    Common risks on this route

    Codepage handling assumed rather than tested

    Validate character-level fidelity explicitly. Counts will not catch it.

    Loss of institutional knowledge

    Few people may remain who understand the configuration. Profiling substitutes evidence for memory.

    Treating archive as out of scope

    If the archive question is deferred, the source system cannot be switched off and the business case does not land.

    How Syntra ETL supports this route

    DataMove

    Extraction, mapping, transformation and load preparation for Oracle Fusion.

    Explore DataMove →

    DataVault

    Source-to-target reconciliation, migration lineage and audit evidence for every cycle.

    Explore DataVault →

    DataLens

    Migration status, data quality and exception visibility across cycles.

    Explore DataLens →

    Proven experience on this migration

    SAP R/3→Oracle FusionMigration complete

    SAP R/3 to Oracle Fusion Cloud for a German enterprise

    A published case study covering this exact source-to-target route.

    View Case Study

    Related migration routes

    SAP ECC→Oracle Fusion

    SAP ECC to Oracle Fusion data migration

    Financials, Procurement, SCM, Master data

    Case study available →    SAP R/3→SAP S/4HANA

    SAP R/3 to SAP S/4HANA data migration

    Financials, Master data, Open items

    View route →    Oracle EBS→Oracle Fusion

    Oracle EBS to Oracle Fusion data migration

    Financials, Procurement, SCM

    Case study available →    SAP ECC→SAP S/4HANA

    SAP ECC to SAP S/4HANA data migration

    Financials, Controlling, Master data, Logistics

    Case study available →

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