New system. Clean data.Same balances.

Application data migration moves the data a business application runs on, such as an ERP, CRM or core banking system, so the business can operate on the new system. Data platform modernization moves analytical warehouses, pipelines and reports to Microsoft Fabric, Databricks or Snowflake. Data Semantics often runs both together, so history from the old application lands on the new data platform.

In Data Semantics programs, AI-assisted migration runs up to 4 to 5 times faster than a manual migration, at around half the cost. AI profiles the source data, surfaces hidden business rules, suggests source-to-target mappings, writes the transformation and load code, fixes failed test loads and runs reconciliations. That removes most of the manual spreadsheet and scripting work, so each test cycle takes days instead of weeks.

Yes, because nothing goes live on AI judgement alone. Every mapping and rule is approved by a named business or technical owner, every code change is tested, and every decision is kept in a decision record that audit can review.

Common routes include Oracle EBS to Oracle Fusion or Dynamics 365, Dynamics AX to Dynamics 365, SAP ECC to SAP S/4HANA, legacy ERPs such as JD Edwards or Sun to NetSuite or Dynamics 365, iMAL, Finacle or FLEXCUBE to Temenos T24 or a new core, Salesforce org merges, Dynamics CRM to Salesforce or the reverse, and OPERA 5 to OPERA Cloud. Other ERPs, CRMs, industry platforms such as Yardi and LS Retail, and homegrown systems are covered on request.

With a data quality phase, typically 4 to 6 weeks, before the first full test load. Data Semantics profiles every source for duplicates, gaps and broken references, ranks issues with Pareto charts and an urgent-versus-important (Eisenhower) matrix, and supports business owners as they fix the few issues that matter most first.

Data Semantics targets opening-balance variance within 0.5% at cutover, and every remaining difference is either fixed as a defect or explained by a recorded, approved decision before sign-off.

Yes. Every mapping, rule decision, test load and reconciliation is recorded, so auditors, regulators and finance can see the evidence at any point, not only in a pack assembled the week before cutover. Each business rule has a migration decision record: what the old system did, what the new one will do, who decided and why, so every difference found at reconciliation traces to either a defect to fix or a change made on purpose. For banks, the evidence is prepared for regulatory review.

Closed history that does not need to move into the new application is archived to your data platform, such as Microsoft Fabric, with its keys and lineage preserved, so it stays reportable and the old system can be retired.

Yes. With migration assurance, your team or partner runs the program while our engineers, with AI-assisted tooling, provide rule discovery, mapping assistance, decision records and independent reconciliation. Or we run the migration end to end.

Data Semantics projects run from 6 weeks for a focused migration, longer for larger programs, because the plan is aligned to your implementation program, its test cycles and its cutover. The data quality phase on its own typically takes 4 to 6 weeks. Pricing is a fixed bid based on the number of data objects in scope, such as customers, suppliers, items, accounts, open balances and history. It starts with a fixed-price Migration Readiness Check, so you know the cost before the work starts.