Data Migration: Moving Your Business Data Without Losing Your Mind

You're switching systems. Years of business data needs to move from the old system to the new one.

Simple, right?

Not usually.

Why Data Migration Is Hard

Data migration looks straightforward on paper. In practice:

• Data is messy. Duplicate customers, inconsistent formats, missing fields, data entered incorrectly years ago.
• Systems think differently. Your old system's "customer" might map to three different concepts in the new system.
• Relationships matter. It's not just records — it's how records connect to each other.
• History is complicated. Do you migrate everything? Just recent data? How do you handle changes during migration?
• Business can't stop. The migration often happens while you're still running the business.

Types of Migration

Big Bang

Everything moves at once. Old system turns off, new system turns on.

When it works:

• Simple data
• Ability to pause operations
• Small data volume

Risks:

• If something goes wrong, everything goes wrong
• Limited time to fix issues
• High stress

Phased Migration

Move data in stages. Maybe customers first, then orders, then products.

When it works:

• Complex data with clear segments
• Need to verify each stage
• Can operate in parallel

Risks:

• Longer overall timeline
• Managing two systems simultaneously
• Data can drift between phases

Parallel Running

Both systems run simultaneously for a period.

When it works:

• Can't afford downtime
• Need to verify new system thoroughly
• Staff need transition time

Risks:

• Double data entry during overlap
• Confusion about which system is "truth"
• Higher cost

The Migration Process

1. Assessment

Before anything else:

• What data exists?
• What's its quality?
• What needs to migrate vs. what can be archived?
• What are the dependencies?

2. Mapping

For each data type:

• Where does it come from?
• Where does it go?
• How do fields translate?
• What happens to data that doesn't fit?

3. Cleaning (Often Forgotten)

Migration is the perfect time to clean data:

• Merge duplicate records
• Standardize formats (phone numbers, addresses)
• Remove obsolete data
• Fill in missing information

Warning: This takes longer than expected. Always.

4. Testing

Run migration on test data first:

• Verify counts (did everything make it?)
• Verify accuracy (did it translate correctly?)
• Verify relationships (are things connected properly?)
• Test edge cases (weird data, old records)

5. Execution

The actual move. Depending on approach:

• Schedule appropriate downtime
• Execute migration scripts
• Verify success
• Have rollback plan ready

6. Validation

After migration:

• Compare old vs. new
• Test workflows end-to-end
• Have users verify critical records
• Document any issues

Common Migration Disasters

"We'll just export to CSV and import"

Sounds simple. Then you discover:

• Character encoding issues
• Nested relationships don't export
• CSV can't handle your data volume
• Import validation rejects half your records

"The migration tool handles everything"

Migration tools help, but they don't think. They'll happily migrate garbage data. They don't understand your business rules.

"We don't need the old data"

Until someone asks about an order from three years ago. Or an auditor requests historical records. Or a legal dispute requires old documents.

"We'll clean the data after migration"

You won't. Once data is in the new system and people are using it, cleanup becomes exponentially harder.

Questions to Ask Your Migration Partner

1. "How do you handle data quality issues?"

   • Good answer: Assess upfront, clean during migration, document decisions
   • Bad answer: We'll deal with it

2. "What's your testing approach?"

   • Good answer: Multiple test migrations, user verification, automated validation
   • Bad answer: We'll run it once and check

3. "How do we handle the transition period?"

   • Good answer: Clear plan for cutover, parallel running, or phased approach
   • Bad answer: We'll figure it out

4. "What if something goes wrong?"

   • Good answer: Rollback plan, backups, documented recovery process
   • Bad answer: It won't

5. "Who's responsible for data validation?"

   • Good answer: Shared responsibility — we verify technical accuracy, you verify business accuracy
   • Bad answer: All you / all us

Migration Costs

Migration is often underestimated. Budget for:

• Analysis and mapping: Understanding what exists
• Cleaning: Fixing data issues (often the biggest cost)
• Development: Building migration scripts
• Testing: Multiple rounds
• Execution: The actual migration
• Validation: Verifying success
• Contingency: Things always go wrong (add 20-30%)

Rough rule: Data migration often costs 20-40% of the total project budget. Don't be surprised.

Your Role

Even with experts handling the technical work:

1. Know your data. What's critical? What's okay to lose? What are the weird edge cases?
2. Allocate time for validation. You need to verify that your business data migrated correctly.
3. Communicate with your team. They'll need to check their data, flag issues, and adapt to changes.
4. Make decisions. There will be judgment calls about how to handle messy data. You need to be available.

The Bottom Line

Data migration isn't just a technical task — it's a business project that happens to involve technology.

The best migrations:

• Assess thoroughly before starting
• Clean data as part of the process
• Test extensively
• Have clear rollback plans
• Involve business users throughout

The worst migrations:

• Underestimate complexity
• Skip cleaning
• Rush testing
• Have no backup plan
• Surprise users with problems

Plan accordingly.

Facing a data migration? Let's plan it properly from the start