u/HorrorPretty1356

Hey everyone,

My team built a data migration tool and I wanted to share what it does. Looking for honest thoughts.

Here’s how it works:

•	It scans both the old system and the new system to read their schemas.  
•	Based on that, it designs the target dataset using the target database.  
•	For mapping fields, you get two options: do it manually, or let the AI suggest the mapping for you.  
•	You can then apply your own transformation rules.  
•	One target table can pull from multiple sources, even when the columns are different.  
•	There’s a report view so you can see the data before and after.  
•	It has data load services to move everything over.  
•	After loading, it gives you a reconciliation report so you can check that nothing was lost or changed by mistake.

The goal was to cut down the manual work and reduce errors during migration, since that part usually takes forever and breaks easily.

A few things I’d like to hear from you:

•	For those who have done big migrations, where do things usually go wrong for you?  
•	Do you trust AI to handle field mapping, or do you still want to check every one by hand?  
•	What would make a tool like this actually useful in your day-to-day?

Happy to answer any questions. Thanks for reading.

Hey everyone,

My team built a data migration tool and I wanted to share what it does. Looking for honest thoughts.

Here’s how it works:

•	It scans both the old system and the new system to read their schemas.  
•	Based on that, it designs the target dataset using the target database.  
•	For mapping fields, you get two options: do it manually, or let the AI suggest the mapping for you.  
•	You can then apply your own transformation rules.  
•	One target table can pull from multiple sources, even when the columns are different.  
•	There’s a report view so you can see the data before and after.  
•	It has data load services to move everything over.  
•	After loading, it gives you a reconciliation report so you can check that nothing was lost or changed by mistake.

The goal was to cut down the manual work and reduce errors during migration, since that part usually takes forever and breaks easily.

A few things I’d like to hear from you:

•	For those who have done big migrations, where do things usually go wrong for you?  
•	Do you trust AI to handle field mapping, or do you still want to check every one by hand?  
•	What would make a tool like this actually useful in your day-to-day?

Happy to answer any questions. Thanks for reading.

I’ve been building a metadata-driven migration platform (Python, API-based) and I’m currently deep in an SAP ECC → S/4HANA project — specifically the Customer/Vendor → Business Partner conversion.

The part I’d love input on is deduplication. We’re using AI-driven matching to consolidate duplicate records into golden records, but tuning the confidence thresholds (false merges vs. missed duplicates) has been tricky.

For those who’ve done large migrations:

•	How do you balance automated merging against manual review?  
•	Any approaches to field-matching that held up well at scale?

Happy to share what’s worked on our end too.