If you’ve worked with data at least once in your life, you’ve probably heard about the data mapping process. Database mapping is crucial for making your next data transition both smooth and efficient.
But how does data mapping work? How does it relate to speed? Aren’t all data migrations fast nowadays? If you're just getting started, reviewing a few data mapping examples can help clarify what your own setup might need.
What is Data Mapping?
Data mapping is the process of matching data fields within a system to specific fields in another system. In help desk migration, you use data mapping to determine how to move tickets, users, statuses, priorities, custom fields, and other objects from the source platform to the target platform. This process maintains data consistency, accuracy, and usability during and after migration, allowing the new system to run with properly matched and organized information.
Example of Data Mapping:
Suppose you migrate from Zendesk to Freshdesk. In data mapping, you define how each field in Zendesk maps to its corresponding field in Freshdesk.
For instance:
- Zendesk's "Ticket Subject" field to Freshdesk's "Subject" field.
- "Requester Email" as "Customer Email".
- A ticket with the status "Open" in Zendesk is mapped to Freshdesk's "Open" status.
- A Zendesk custom field "Product Type" is equated with a Freshdesk instance custom field "Product Category."
- The Zendesk "Assignee" with the Freshdesk "Agent" field.
This way, all the critical data remains accurate and functional after the migration.
Why Do You Need Data Mapping?
Now that we’ve covered the basics of data mapping, let’s explore why it’s such a critical step in migration. Proper data mapping matters, but these three reasons are key to a successful transition.
Data Integration
Data integration is the process of combining data from different source systems into a target system in an integrated and consistent manner. It entails data mapping or field correlation from the source system to equivalent fields in the target system for proper data transformation.
When you map data accurately, you ensure the correct transfer of tickets, users, fields, attachments, and tags—preserving integrity, consistency, and full functionality in the target system.
Before you begin your integration process, use a data mapping template to understand how each field in your source system aligns with fields in the target platform.
Data Migration
To move data between platforms, you need to adjust it so the new system can recognize and interpret it. But that is just halfway through.
Data mapping plays a key role in data migration by placing every piece of information in its correct location. Unless you map your data correctly, you risk creating inaccurate results and damaging valuable information, issues that are time-consuming and difficult to fix.
Even if you maintain data integrity, poor mapping can misalign records, like assigning the wrong customer details and confusing Jane Doe with John Doe. By establishing a reliable data mapping process, you safeguard your data, maintain operational accuracy, and ensure a smooth transition to your new platform.
Data Preservation
Data preservation is crucial and often more complex than it seems—let’s break it down.
Over time, you may accumulate excess data that you don't need right away but must preserve for future use or compliance.
In these cases, exporting to external storage, like a hard drive or cloud, is common. But, without proper planning, retrieving that data can become difficult. That’s why data preservation needs the same strategic approach as active migration.
Data preservation ensures that all essential information remains intact and usable throughout the migration process. Without careful mapping, you can lose, change, or misread important data, undermining its quality and reliability.
Effective data mapping helps preserve historical records, metadata, custom fields, and user-generated content. By clearly defining how they migrate each data element to a new system, organizations ensure continuity, reduce errors, and maintain compliance. In short, precise mapping protects the value of your data during the transition.
You need to map the data accurately to use transfer tools effectively and place everything where it belongs, which leads us to the next section.
What Are the Techniques?
Now that you’ve learned what is data mapping and what is the purpose of it, let’s briefly look at your options. And the options you have. There are three ways you can map your stuff, manually, semi-automatic, and automatically. Now we won’t be listing any recommendations in regards to tools but what we will do is point out the pros and cons of each method. So, here’s how each system stacks up against each other.
Figure 1: Pros & Cons
| Method | Pros | Cons |
| Automatic | Fast | Costs money & prone to errors |
| Semi-automatic | Kinda Fast & Pretty Accurate | Also costs money but slightly less |
| Manual | Accurate & Free | Slow |
These are far from all the pros and cons but the general idea is there. If you go with the automatic method, you will no doubt save a lot of time but it is costly and if you have an obscure system, you might find some inconsistencies. Then there is semi-automatic which also costs money but is much more accurate. This is perhaps the best of both worlds as it is not as slow as manual and it does allow you to correct stuff mid-process (most of the time at least).
Bottom Line
And that’s all for today. There are many things we can talk about (like how mapping software can help you save money and what are the caveats of mapping) but this should be enough to get you started. And speaking of getting you started, in case you need to move your stuff from one platform to another, we can help you out. And if you are worried about the lack of data mapping, then no need to be worried, we got you covered. Just drop us a message and we’ll send our top specialist to help you out. But for now, thanks for joining!
