Data Migration in Dynamics 365 — the comprehensive guide to secure, clean and efficient ERP migration projects – Part 2

In part one, we discussed what needs to be prepared for a successful data migration. But how does it proceed? 

Testing & validation — multi-stage and automated  

Testing is the key lever for minimising risks. A multi-stage test architecture makes sense: unit tests of the transformation logic, integration tests of the entire data pipeline, end-to-end test migrations in a staging environment and, finally, user acceptance tests (UAT) with the department managers. Each test migration should be completed with a reconciliation: Do the counters, balances and official key figures between the old and target environments match? Automated validation reports, e.g. sum comparisons, number of imported rows per entity, failed validations, facilitate traceability.  

Allow time for multiple iterations. Tests often reveal unexpected inconsistencies. If you plan too conservatively here, you will experience unpleasant surprises in live operation. 

Go-live & cutover: Process, communication and contingency plan  

The go-live is not a single process, but an orchestrated sequence with prepared checklists: Freezing of master data in the old system, final export of delta data, loading into the target environment, validation steps, approval by the specialist departments and communication to all affected teams. Define a migration window and a communication chain: Who is responsible after the cutover, what are the escalation levels, and what is the backout scenario if critical errors occur?  

A backout plan should be in place, but it is rarely used. Even more important is a detailed plan for quick rework (hotfixes) and so-called ‘hypercare support’ after go-live, in which specialists accompany the first few days, quickly fix errors and make detailed adjustments.  

After migration: stabilisation, archiving and governance 

Migration does not end after successful loading. Stable monitoring, data quality checks in the first weeks of operation and a governance organisation ensure long-term success. Archiving strategies must be implemented: Which data remains in the live system, and which is transferred to an archive or data warehouse? Reporting controls should ensure that key figures are consistent. 

In addition, a permanent data stewardship programme is recommended: Responsible parties monitor and continuously improve data quality, maintenance processes and authorisations. 

Security, data protection and compliance 

When transferring personal or sensitive data, data protection requirements (e.g. GDPR) must be observed. Masking or pseudonymisation in test environments, encrypted transfers, secure storage and access concepts are mandatory. Also check retention periods, any legal requirements for financial data and the requirements of external auditors. 

Common pitfalls — and how to avoid them 

Many migrations fail due to similar issues: incomplete scoping, insufficient testing, poor data quality, unclear responsibilities and overly tight cutover plans. These problems can be avoided with a clear migration concept, sufficient resources for cleaning and testing, clear roles, and a coordinated communication concept. Technically, a modular pipeline with repeatability helps — this allows errors to be quickly located and corrections to be rolled out automatically. 

How EDI (Electronic Data Interchange) relates to migration 

EDI is an ongoing exchange of data between partners — it is not a substitute for migration. If your legacy system had EDI connections to customers and suppliers, these connections must either be re-established in the new system or continue to run via bridges. During a migration, it is often necessary to check whether EDI partners will remain connected to the legacy system during a transition phase (hybrid operation) or whether EDI traffic will be switched to the new system immediately. Dual solutions, message brokers or middleware can help to control EDI flows cleanly and synchronise them during the cutover.  

Budget, time frame and effort — what you need to be prepared for 

There are no blanket statements about the duration of a migration — it depends on data volume, the complexity of the business logic, the number of source systems, data quality and internal decision-making processes. Small projects (one module, clean data) can be implemented in weeks; complex subsidiaries with extensive historical data, interfaces and compliance requirements take months to over a year to prepare and implement. Allow for buffers for testing, rework and stabilisation.  

Brief description of practical example (typical procedure) 

In a typical project, stakeholders are first involved and an assessment is carried out. This is followed by data profiling and the definition of the scope of migration. In iterative cycles, mappings are developed, test data is cleaned up and several test migrations are run. After final validation, a go-live window is planned in which delta data is exported, loaded and verified. The first few weeks after go-live are run under hypercare conditions with rapid support and focused troubleshooting. 

How an external partner can support you efficiently 

An experienced migration partner brings methods, reusable tools and best practice templates that accelerate your project and reduce risks. Typical services provided by a specialised service provider include: an initial data readiness assessment, implementation and configuration of the data management framework, development of mapping scripts and ETL pipelines, automation of test runs and reconciliation reports, as well as operational support during go-live and subsequent hypercare. An external partner also helps to establish project governance, train data stewards, and implement long-term governance processes so that data quality does not end with the project.  

Everware Consulting can take on specific tasks in this context: We conduct a structured assessment, create a detailed migration concept including risk and rollback scenarios, and set up standardised, repeatable migration pipelines. Technically, we work with the mechanisms recommended by Microsoft (Data Entities/DMF), supplementing them as needed with Azure-based orchestration or proven third-party connectors, and take care of the testing, go-live and hypercare phases. Our experience from several migration projects allows us to quickly identify recurring pitfalls and implement pragmatic, reliable solutions — from cleaning up large customer databases to automated transfer of open items.  

FAQ — Answers to the most important search queries 

How do I migrate data to Dynamics 365? 

Define the scope, perform data profiling, clean up data, create mapping rules, perform multiple test migrations, and plan a careful cutover with hypercare support. Use Data Entities/DMF for standardised imports and supplement with ETL tools as needed. 

What is the best migration tool for D365? 

For standard cases, the integrated Data Management Framework (DMF) is the first choice. For complex transformation and orchestration requirements, Azure Data Factory, SSIS with appropriate connectors (e.g. KingswaySoft) or specialised integration platforms are suitable additions. The choice depends on the scenario, the environment (cloud vs. on-premises) and the licensing framework. 

Should I migrate historical transactions? 

Only if they are required for operational purposes or for compliance reasons. Common practice: migration of recent years and archiving of older data in a data warehouse with reporting access.  

How long does a migration take?  

This depends greatly on the scope and complexity. Small modules can be implemented in a few weeks, while complex corporate migrations can take several months to a year. Plan for iterations and sufficient testing time.  

Is direct DB access possible for the migration? 

Direct SQL access is not usually provided for cloud SaaS tenants. Use supported methods such as data entities/DMF, OData APIs or integration

 services. On-premises installations often allow direct DB access, but this can raise support and security issues. 

Conclusion 

A successful data migration is manageable, repeatable, and controllable — provided it is treated as a project with clear responsibilities, iterative testing, and clean data quality. With the right combination of strategy, tools, and experienced partners, you will ensure that your Dynamics 365 system provides reliable information from day one and that your company realizes the promised efficiency gains.

If you wish, this guide can be transformed into a concrete migration concept for your company — including an assessment of data quality, a timeline with milestones, and a risk analysis for your specific use case. Just reach out to us!