With the focus on digital transformation, customer/employee experience and AI, data is getting more attention than ever. This makes it even more surprising that one of the most overlooked processes when migrating data is validation! But, difficult to believe or not, it is the case and one of several reasons that, as Gartner research has shown, 83% of data migration projects either fail outright or fail to meet time and budget expectations.
Why is Data Validation getting overlooked?
What can be going wrong? Data validation is hardly rocket science. I mean all you need to do is to check that all the data you expected to be migrated from the source system to the target system has got there. So why is it getting missed?
Well, as is often the case, the devil is in the detail. Many migrations involve a lot of data and on top of that, the data might have needed to be restructured and transformed to fit in the new system. This means it is not as simple as comparing the source and target.
In fact, in most cases, it simply is not practicable to do any significant data validation manually. This is why data validation may just involve picking a few records on the source and seeing if they look right on the target. This is where the problem starts.
So, what’s happened to my data?!?
We have been called into many data migration projects where significant chunks on data just seem to have disappeared! You can probably imagine the state of mind of those who rely of the data that has gone missing – not that happy. Especially when they have been told “It’s all done everything is there for you on the new system.” then to find it anything but. This is what can happen when you don’t do comprehensive data validation.
What are the other problems that can be missed?
Some types of problems that can be missed without comprehensive data validation:
Data-type mismatches, such as text data in numeric columns
Incorrect column mapping, such as phone numbers in email address fields
Missing objects, such as attachments and knowledge-base articles
Incorrect foreign-key references, such as assignment- or approval-group membership
If Data validation is just some spot-checking here and there these are just some of the issues that can get missed. This is why comprehensive validation is so important.
Validate, validate, validate!
Comprehensive data validation can really save the day – taking a potential failed migration to a great success.
A key element is the right data migration automation solution and, funnily enough, that is what we do! Precision Bridge’s automated data migration tools and make your migration faster, easier and more reliable with comprehensive data validation. So you can look forward to lots of thanks rather than irate users asking what you’ve done with their data!
To learn more about data migration automation and how Precision Bridge tools can help, contact us today.