What are the business drivers and how will the project be funded? Data migration can involve many different business units, so collaboration will be needed.

The key issues to identify are:

• Is there a hard-stop date by which this migration must be complete?
• What is the impact to the business if the project is not complete by the deadline?
• What risks do you see with migrating the data (volume, multiple data sources, data quality issues, system access)?
• Who owns the budget for the project, what is the budget, and when is it available?
• Other than the budget holder, are their other decision makers in the project?
• How will the project be managed (project manager, team, steering committee) and who has the final say?
• How will you measure the success of the data migration?

• Identify Source and Target systems
• Have the systems been in production for a period of time?
• Define any validation rules for data extraction and data load (ie only extract open or active records, all data since 2008)
• Define error handling (what to do if fields fail, ie fail the entire record or process partial records)
• Define record ownership in target system(s)
• Document testing approach (especially relevant if you only have production systems and no sandbox environments)
• Document stakeholders and system owners
• Identify key risks
• Define success criteria

• Document data sources, versions, locations, accessibility
• Identify customizations in source systems, do these customizations have to be replicated in the target system
• Do you have specific data validation rules in the source system that do not exist out of the box in the target system?
• Define objects and fields to be migrated
• Size of the data to be migrated
• Extraction process, tools and resulting format
• If you are going to do multiple data extractions, can you easily extract data deltas, ie extract for different time periods?
• Data relationship and dependencies
  
  • determine the order of migration
• Data quality, document any data cleansing and de-duplication required, determine if there needs to be an intermediary data store to make data cleansing easier
• Data mapping and data transformation
• Data load estimate

• Document any business constraints (especially if you are dealing with production systems)
• Rollback impact
• Communication plan
• Impact to any support processes
• Change control
• Resource availability for source and target systems

• Pre-migration test with sample data
• Adjust time lines and tasks based on test

• Migration checklist
• Success criteria
• Time required and tasks for:
  
  • Data extract
  • Data cleansing
  • Data mapping and transformation
  • Data load (Calculate the time involved to migrate the data including any testing and fall back contingencies you need)
• Customizations or changes required for target system
• Rollback plan
  
  • Contingencies and rollback activities
• Key activities and owners
• Communication plan