Artificial Intelligence
The Complete Data Migration Checklist for 2026
Learn how to ensure your team is prepared with clean, trusted data for a successful system migration.
Blaise Radley
Editorial Strategist
Workday
A new enterprise system can only be as reliable as the data behind it.
But many organizations still struggle with information spread across legacy systems and teams. According to PwC, 63% said that fragmented and complex data makes compliance more difficult, while 56% cited data reliability and quality as a challenge.
Those issues can quickly become amplified during migration. Inconsistent user profiles and HR records can disrupt payroll and system access, poorly mapped financial schemas can undermine reporting, and incomplete supplier, cost center, or IT integration mapping can create downstream failures in automated approval workflows, payments, and analytics.
A data migration checklist helps teams address these kinds of risks before go-live, giving the new system a data foundation teams can trust from day one.
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What Is Data Migration?
Data migration is the process of moving information from one system or storage environment to another. It often happens during ERP or HRIS implementations, cloud migrations, system consolidations, and other major technology changes.
For IT, HR, and finance teams collaborating on a migration, that information can include:
- Employee, payroll, benefits, and compensation records
- Organizational structures and reporting hierarchies
- General ledger, chart of accounts, and core financial data
- Supplier, customer, and third-party vendor integration records
- Budgets, fixed assets, transaction history, and system audit logs
- Tax, regulatory compliance, security, and governance data
But migration involves more than transferring files from one place to another. Before data is ready for the new system, it often needs to be cleaned, standardized, transformed, mapped to new fields, and validated.
These steps can be challenging, especially when teams are working across disconnected systems: 84% of leaders cited integrating HR, payroll, and finance systems and manually reconciling conflicting data between them as a major operational pain point and their single biggest time sink.
Data migration can expose problems that have built up across legacy systems over time. When that happens, teams may spend the first months after launch correcting issues instead of getting value from the new system.
Data Migration Checklist: Steps Before and After Go-Live
A successful migration depends on decisions made well before the final data load. IT leaders, enterprise architects, and business data owners need to align on how to handle large datasets during migration.
Use this checklist to guide the migration from early planning through post-go-live review:
Make a Pre-Migration Plan
Start by defining the scope, ownership, and standards for the migration. This helps prevent teams from moving unnecessary data, relying on unclear rules, or discovering ownership gaps too late.
Define the migration scope. Identify which systems and records need to move, how much historical data is required, and what can be archived or retired.
Assign data owners. Make clear who owns IT technical execution, HR and Finance business domains, and shared enterprise data definitions.
Inventory data sources. Document where relevant information currently lives, including legacy systems, spreadsheets, databases, and connected applications.
Set retention requirements. Determine which records must remain available for operational, regulatory, tax, or audit purposes.
Establish data standards. Agree on field definitions, naming conventions, formats, and authoritative values before data is transformed.
Prepare the Data
Once the scope of the data migration is clear, focus on improving the quality and usability of the data before it enters the new system.
Remove duplicate and obsolete records. Avoid moving unnecessary data and known quality problems into the new system.
Resolve missing information. Identify required fields and determine how incomplete records should be handled.
Standardize inconsistent data. Align formats, codes, classifications, and naming conventions.
Resolve conflicting records. Decide which source should be treated as authoritative when systems contain different values.
Document data mappings. Define where each legacy field belongs in the new system.
Set transformation rules. Document fields that need to be reformatted, combined, split, or converted before loading.
Secure the Migration
Enterprise data migrations involve highly sensitive employee, payroll, vendor, financial, and system access data. Security should be built into the migration process from the start, not treated as a final review.
- Limit access to migration data. Give people access only to the information required for their role in the project.
- Protect data during transfer and storage. Apply appropriate controls to extracts, staging environments, and migration files.
- Plan for temporary data. Decide how test datasets and intermediate files will be stored and deleted when they are no longer needed.
- Validate new-system permissions. Confirm that business users, system administrators, and integrated applications can access necessary information without violating security policies.
Test and Validate
Testing should prove that the migrated data works in the context of real IT architecture, system integrations, and end-to-end business processes, not just that the load completed.
- Run test migrations. Use representative data before performing the final load.
- Compare migrated records with source systems. Check for missing, incomplete, or incorrectly transformed information.
- Check IT infrastructure and security data. Review user identities (IAM), Single Sign-On (SSO) profiles, security permissions, active directory roles, and system configuration settings.
- Validate HR data. Review employee counts, compensation, employment status, reporting relationships, benefits, and effective dates.
- Reconcile finance data. Confirm account balances, open transactions, supplier and customer records, assets, and reporting structures.
- Document discrepancies. Trace errors back to the source record, mapping rule, or transformation logic.
- Retest after corrections. Repeat validation until material differences are resolved.
Prepare for Cutover
Cutover is the point where planning, testing, and ownership come together. Teams should know exactly when legacy activity stops, when the final load happens, and what must be true before the new system becomes the system of record.
- Set the system freeze period. Determine when users will stop entering information into legacy systems.
- Schedule the final extract and load. Define the sequence, timing, and owner for each cutover activity.
- Establish approval criteria. Decide what must reconcile before the new system can become the system of record.
- Create a contingency plan. Document what the team will do if a critical problem appears during migration.
- Communicate the transition. Make sure affected teams understand the timing and any actions required from them.
Reassess After Go-Live
Migration does not end when the new system launches. Teams should continue checking data quality, process performance, and ownership after go-live.
- Perform a final reconciliation. Confirm that key records and totals remain accurate after launch.
- Test critical processes. Verify system integrations, automated data pipelines, access controls, payroll runs, and other essential IT, HR, and finance workflow.
- Confirm user access. Make sure employees and administrators can reach the correct information.
- Track migration issues. Assign owners to post-launch defects and data-quality problems.
- Maintain data governance. Keep ownership and quality standards in place once the migration project ends.
Migration Mistakes to Avoid
Even with a detailed checklist, migration can go off track when teams treat it as a technical transfer instead of a business-critical data project.
One common mistake is treating migration purely as an isolated IT transfer without involving HR and Finance data owners. These teams understand the meaning, context, and business rules behind their data, so they need to be involved in mapping and validation. Another is migrating everything by default, which can carry outdated records, duplicate entries, and unnecessary complexity into the new system.
Timing also matters. If teams wait too long to clean data, test real business outcomes, or reconcile migrated records against source systems, they may not discover problems until after go-live. And because enterprise HR, finance, and user access data includes highly sensitive employee, payroll, vendor, and system configuration records, security needs to be built into the migration pipeline from day one.
The principle is simple: treat migration as a critical readiness exercise, not just a transfer of information. The goal is to enter the new system with data that is accurate, governed, and ready to support the business.
When teams trust their system data, they spend less time correcting preventable errors and more time using the platform to support the business.
Build a Stronger Data Foundation
A major platform migration gives IT, HR, and finance leaders a shared opportunity to break down silos and modernize enterprise data. During migration, teams can decide which records still matter, which sources should be trusted, and how information should be managed going forward.
That work helps prevent old data problems from following teams into the new environment. Outdated records, inconsistent definitions, unclear ownership, and poorly mapped fields can create reporting issues, process delays, and extra cleanup after go-live.
The payoff comes after implementation. When teams trust the data in the system, they spend less time reconciling reports or correcting preventable errors and more time using the platform to support the business.
Fifty-one percent of CFOs rely on non-financial data, yet only 52% of CIOs have a unified view of company data. Bridge this gap for smarter reporting by downloading our 10-step guide.
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