A large enterprise organisation headquartered in Düsseldorf used Syntra ETL to migrate critical business data out of a legacy SAP R/3 environment and into Oracle Fusion Cloud, as part of a broader cloud transformation and legacy-system modernisation programme. Syntra ETL provided the end-to-end framework: R/3 extraction, mapping of legacy structures to Oracle Fusion objects, transformation and cleansing, automated pre-load validation, Oracle-compatible load-file generation, exception management and reconciliation across multiple data cycles.
SAP R/3 is not simply an older ECC. It predates the conventions that modern migration tooling takes for granted, and a system still running R/3 has usually been running it for a very long time — which means decades of accumulated configuration, custom development and data whose original owners have long since moved on.
The central difficulty was the distance between the two models. Legacy R/3 structures had to be mapped onto Oracle Fusion objects while preserving the data relationships, the business context and the historical integrity that make the records worth migrating in the first place. A field moved without its context is not migrated data; it is a value in a column.
For a German enterprise there is a further constraint that catches teams out: older R/3 installations are frequently non-Unicode. Umlauts, sharp s and other extended characters are stored under a legacy codepage, and an extract that ignores this produces corrupted names and addresses that pass every count-based reconciliation while being visibly wrong to anyone who reads German.
Legacy SAP modernisation is an archaeology problem before it is a migration problem.
R/3 structures had to be interpreted and mapped onto Oracle Fusion objects rather than exported and reshaped by hand, so the conversion was repeatable across every migration cycle.
Relationships between records carry the business meaning. They were maintained through extraction and transformation so data arrived in Oracle Fusion connected, not flattened.
Historical data had to survive the same translation as current data, keeping the record the business and its auditors still depend on intact through the move.
Data was transformed and cleansed as part of the pipeline, with corrections applied through repeatable rules rather than one-off edits that cannot be reproduced in the next cycle.
Automated pre-load validation raised structural and data-quality issues as reportable exceptions ahead of the Oracle load, keeping each cycle productive.
Source-to-target traceability was maintained throughout, so every migrated value could be traced back to the R/3 record it came from.
One controlled, repeatable pipeline run across multiple data cycles, with reconciliation and traceability at each pass.
Syntra ETL provided the migration framework end to end rather than a point tool for one stage of it.
R/3 is a generation older than ECC, and four of its characteristics shape the whole extraction design.
Non-Unicode codepagesMany R/3 installations were never converted to Unicode. Text is stored under a legacy codepage, so umlauts, sharp s and other extended characters need explicit conversion on extract. Skip it and names and addresses arrive corrupted — while every record-count reconciliation still reports success, 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, and segment reporting handled through special ledgers. The financial model the extract is reading is not the one Oracle Fusion expects, so the reconciliation design has to account for how totals were kept, not just what the line items say.MANDT — client partitioningAs in ECC, application tables are client-dependent with the client as the leading key. An extract that does not constrain it can blend production with test and training data into a set that reconciles perfectly against itself and is still wrong.Check tables and domain valuesCodes are validated against check tables and domain fixed values rather than stored with their labels. Reference and text tables are extracted alongside the transactions, or the migrated data is uninterpretable the moment R/3 is switched off.ADK archive filesData already archived out of R/3 through SAP's archiving lives in ADK archive files, not in the database. If that history is in scope it has to be read through the archive layer rather than assumed to be reachable by SQL — 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. These are found through profiling rather than assumed away, because they are invisible in any standard object list.Oracle Fusion does not take direct database writes. Data enters through defined load utilities that stage into interface tables and then import into base tables, and each stage rejects independently.
The three-point comparison is what catches the failure that matters. 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.
One platform, three products, each doing a distinct job on the same programme.
SAP R/3 extraction, mapping, transformation, cleansing, validation and Oracle Fusion load-file generation.
Source-to-target reconciliation, migration lineage and the audit evidence behind each cycle.
Migration visibility across cycles — records processed, validation exceptions and reconciliation status.
What the modernisation programme delivered.
Prospects planning a comparable programme usually want a sense of scale before discovery. The ranges below are what a migration off a mature SAP estate at roughly $2bn revenue typically involves.
These are planning ranges, not this customer's figures. They are typical planning ranges for an enterprise of roughly this size, published to help you size your own programme. Actual scope is established during discovery and varies widely by sector — a manufacturer and a services business at the same revenue carry very different data profiles.
Tell us which modules are in scope, how much history has to move and your target platform, and we will walk you through how this modernisation was run.
Similar Projects
Selected by shared source platform, target platform, industry and project type.