Fast answer
The data migration planner gives you a complexity score, estimated time, recommended approach, and specific tools for automating a transfer once you select your source and target systems. The complexity score from 1 to 10 factors in schema compatibility between source and target, the number of field types requiring transformation such as dates, picklists, and relationships, volume sensitivity, and whether linked records like contacts-to-companies keep their associations. It covers the 10 most common business systems with specific paths for common pairings like HubSpot to Salesforce or Sheets to Airtable, and provides a general framework for pairs outside its database. For scores 1 to 4, self-service is feasible in a few hours; scores 5 to 7 suggest a freelancer or migration service; scores 8 to 10 warrant a specialist because data-loss risk rises with complexity. To avoid data loss, keep source data read-only for 30 to 90 days, test with a small batch first, validate record counts, spot-check individual records, and migrate during low-activity hours.
On this page
What this page covers
A tool visitor should leave with a decision, not just a number: build now, prepare first, choose another workflow, or follow a course path.
- 01Systems
- 02Complexity
- 03Plan
- 04Tools
Why does this matter now?
Select your source and target systems. Get a migration complexity score, estimated time, recommended approach, and specific tools for automating the transfer.
Internal path
Where to go next from this page
These links are part of the A8gent learning and conversion path. Use them to move from concept, to diagnosis, to workflow build, to course.
What you should be able to do after this
- Complexity score
- Time estimate
- Migration approach
- Tool recommendations
How do you do it, step by step?
1. Get started
Select your source and target systems. Get a migration complexity score, estimated time, recommended approach, and specific tools for automating the transfer.
What mistakes should you avoid?
- Not understanding: How is the complexity score calculated - The complexity score (1-10) factors in: schema compatibility between source and target (how different are the data models), number of field types requiring transformation (dates, picklists, relationships), volume sensitivity (whether the migration is simple regardless of record count or becomes harder at scale), and relationship preservation (whether linked records like contacts-to-companies maintain their associations after migration).
- Not understanding: Can I migrate data between any two systems - Our planner covers the 10 most common business systems and provides specific migration paths for common pairings (like HubSpot to Salesforce or Sheets to Airtable).
- Not understanding: Should I hire someone or do the migration myself - For complexity scores 1-4: self-service is feasible with our recommended tools and 2-8 hours of work.
FAQ
How is the complexity score calculated?
The complexity score (1-10) factors in: schema compatibility between source and target (how different are the data models), number of field types requiring transformation (dates, picklists, relationships), volume sensitivity (whether the migration is simple regardless of record count or becomes harder at scale), and relationship preservation (whether linked records like contacts-to-companies maintain their associations after migration).
Can I migrate data between any two systems?
Our planner covers the 10 most common business systems and provides specific migration paths for common pairings (like HubSpot to Salesforce or Sheets to Airtable). For pairs not in our database, we provide a general migration framework with universal best practices. The core approach (audit, map, clean, test, migrate, validate) applies regardless of the specific systems involved.
Should I hire someone or do the migration myself?
For complexity scores 1-4: self-service is feasible with our recommended tools and 2-8 hours of work. For scores 5-7: consider hiring a freelancer or using a migration service ($500-2,000 depending on volume). For scores 8-10: engage a specialist consultancy or the target vendor's professional services team. The risk of data loss increases with complexity, and professional help prevents costly mistakes.
How do I avoid data loss during migration?
Five critical practices: (1) Never delete source data until migration is verified (keep it read-only for 30 days). (2) Test with a small batch (10-20 records) before full migration. (3) Validate record counts match between source and target. (4) Spot-check 5-10 individual records for field accuracy. (5) Run the migration during low-activity hours to avoid conflicts with live data entry.
What about ongoing sync after the initial migration?
If you need both systems to stay in sync post-migration, you need a different approach than one-time transfer. Tools like Zapier, Make, and Autonoly can maintain bidirectional sync between systems. However, bidirectional sync adds significant complexity (conflict resolution, duplicate handling). Consider whether you truly need sync or whether the migration is a one-way, one-time move.
How long should I keep the old system active after migration?
Minimum 30 days, ideally 90 days. Keep the source system in read-only mode as a backup and reference. During this period, run parallel checks: compare key reports between old and new systems to catch discrepancies. After 90 days with no issues discovered, you can safely decommission the old system. Some teams keep archives permanently for compliance, depending on data type and industry.
Sources & further reading
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