Migrating project management data between tools like Jira, Linear, Asana, Monday.com, Trello, ClickUp, and Notion is a complex process that hinges on the quality of your data. Before beginning any migration, it is essential to clean and prepare your project data to ensure a successful transition, minimize data loss, improve team adoption, and maintain compliance. This guide will walk you step-by-step through the preparation process, best practices, and actionable techniques to get your data ready for any project tracker export or data archiving need.

Why Data Cleaning Matters During Migration

Project management tools are central to team collaboration, task tracking, and organizational workflow. Over time, these tools accumulate a lot of legacy data, redundant entries, outdated tasks, and inconsistently formatted information. Migrating unclean data can result in:

  • Data duplication and clutter in the new tool
  • Lost or orphaned records
  • Compromised reporting and search capability
  • Breach of compliance requirements due to misplaced sensitive information
  • Poor team adoption due to loss of trust in migrated data

Preparing, cleaning, and validating your data before migrating to a new project management platform is foundational for a streamlined migration process and ongoing project success.

Step 1: Audit Your Project Data

Begin with a comprehensive data audit to understand the scope and characteristics of your project data. This involves:

  • Listing all active and inactive projects, boards, or workspaces across your tools
  • Reviewing all record types: tasks, issues, tickets, comments, attachments, custom fields, and user accounts
  • Identifying data sources, integrations, and linked systems contributing to your project data

Use your tool’s reporting features or static export functionality to generate data inventories, which help highlight the volume and variety of content to be reviewed.

Step 2: Identify Redundant and Obsolete Items

Over time, project tracking tools tend to accumulate:

  • Duplicate issues or tasks created by different team members
  • Outdated or closed projects that are not in active use
  • Archived tasks that no longer need retention
  • Old sprints, milestones, or epics with no current relevance

Systematically review these items. Tools like Jira and Asana offer search filters to surface closed or aged records. Make lists of redundant items to be deleted, merged, or archived using static exporting before migration.

Step 3: Standardize Data Formats

Data formatting inconsistencies are a primary migration pitfall. Typical format mismatches include:

  • Dates in different formats (MM/DD/YYYY vs. DD/MM/YYYY)
  • Inconsistent user naming conventions (email, full name, initials)
  • Varying priority, status, or custom field values

To avoid failed imports or mapping errors, define a standard for each data type. Normalize values so that, for example, statuses in Trello (“To Do/Doing/Done”) align with those in Monday.com (“Not Started/In Progress/Complete”).

Step 4: Validate User and Permission Lists

People data, such as assignees, reporters, and watchers, should be accurate and up-to-date. Problems might include:

  • Inactive users still assigned to tasks
  • Users with unmatched emails or display names across different tools
  • Incorrect permissions that may expose sensitive data during migration

Reconcile user lists to ensure each active user has a corresponding and correct profile in the target tool. Remove or replace accounts for staff who have left the organization, and review permission levels so only the right data and users are carried forward.

Step 5: Purge Unnecessary Attachments and Comments

Project management data often includes large volumes of attachments, screenshots, and comment histories. These can slow down migrations and lead to inflated storage use in the new tool. Take the time to:

  • Remove duplicate or versioned file attachments
  • Archive or export critical documents for compliance before bulk deletion
  • Trim comment threads that add little value or carry outdated information

For compliance, retain relevant records using the static export feature before removing them from the project management tool.

Step 6: Address Compliance and Sensitive Data

Certain project data may contain personally identifiable information (PII), business-sensitive documents, or regulated data that must be handled with care. Ensure your cleaning process:

  • Identifies all sensitive fields and records
  • Follows your organization’s data retention and privacy policies
  • Documents all deletions and modifications for audit purposes

If you are migrating to tools like Notion or ClickUp that have different data control models, confirm compliance requirements are still met post-migration.

Step 7: Verify Integrations and Dependencies

Many teams connect their project management tool with CRMs, code repositories, or automation platforms. Before migration, check:

  • Which integrations link to data that is being migrated
  • If workflows rely on external data that must be cleaned or reconnected
  • That dependencies (for example, references to Git commits in Jira tickets) are maintained or mapped correctly in the target tool

Flag and resolve issues where integrations may break or produce orphan data during migration.

Step 8: Test With a Sample Migration

Before migrating all your cleaned data, perform a sample migration with a subset of records. This allows you to:

  • Verify mappings between old and new fields
  • Detect formatting or compatibility issues early
  • Gather feedback from a focus group of end users

Adjust your cleaning process based on the results, and ensure quality by repeating the test if necessary.

Step 9: Document the Cleaning Process

Maintain detailed documentation of:

  • The scope of data included in the migration
  • Records and items purged, archived, or modified
  • Rationale for decisions (e.g., compliance, redundancy, usability)
  • Steps completed at each stage

Good documentation ensures transparency, simplifies troubleshooting, and provides a record for compliance audits.

Conclusion

Cleaning your project data before migration is a best practice that minimizes risk, ensures continuity, and makes the most of your new project management tool’s capabilities. By following these nine steps—auditing, de-duplicating, standardizing, validating users, purging attachments, addressing compliance, reviewing integrations, testing, and documenting—you can achieve a smooth and successful migration.

Whether you’re migrating between Jira, Linear, Asana, Monday.com, Trello, ClickUp, or Notion, effective project data cleaning is the foundation for effective project tracker exports, seamless data archiving, and future-proof project management. Start your migration journey with a clean slate for maximum productivity and compliance.