Oracle Fusion data migration is the process of extracting, cleansing, transforming, and loading data from legacy ERP systems, such as Oracle EBS, JD Edwards, SAP, or other on-premises platforms, into Oracle Fusion Cloud. It is consistently one of the highest-risk phases of any Oracle Cloud ERP implementation, yet it remains one of the most underestimated.

Get it right, and your new system is accurate, trusted, and ready to deliver value from day one. Get it wrong, and even the most carefully designed Oracle Fusion deployment becomes unreliable from the moment you go live.

This short guide is based on our consultants' real-world experience. We know what 'good' data migration looks like, and we also understand why it is so often mishandled.  

Why Does Oracle Fusion Data Migration Fail?

Poor data quality is like rust. It's invisible at the start, spreads quietly, and by the time you notice it on go-live day, the damage is already done.

"We'll sort the data later," is the most expensive sentence in any ERP project. "Later" arrives sooner than you think, and it is usually on go-live day, when all eyes are on you and your team. Keep in mind, bad data migrated is bad data multiplied.

The Most Common Failure Points

• Underestimating legacy data complexity. Enterprise data built up over years in JD Edwards, E-Business Suite, or bespoke systems is rarely clean, consistent, or well-documented. Fields are repurposed. Duplicate records accumulate. Business rules exist only in the memory of long-serving staff.
  
  
  
• Treating cleansing as optional. Organisations often want to "just move the data across." The reality is that migrating uncleansed data doesn't solve the quality problem; it imports it directly into the new system, where it surfaces immediately in reports, processes, and integrations.
  
  
  
• No clear data ownership. Without defined data stewards, people who are accountable for specific data domains, decisions stall, exceptions pile up, and the migration drags.
  
  
  
• Over-reliance on scripts and spreadsheets. Many implementation partners handle data migration reactively: writing one-off scripts, passing data through spreadsheets, and addressing issues as they emerge rather than preventing them through a governed process.

One of the most overlooked ways to reduce migration complexity is encouraging clients to close out open transactions ahead of the cutover date, paying outstanding invoices early, clearing aged payables and receivables, and settling open purchase orders where possible.

It rarely gets discussed openly, because clients will often take a small financial hit when payments fall outside normal payment windows. But the payoff is real: fewer open items to migrate, a cleaner opening balance, and significantly less noise in the validation process.

If your cutover window is tight, clean books matter as much as clean data. Have the conversation early, before anyone has committed to a go-live date.