Though the article is more than 5 years old, it still aligns with what we are seeing in the field today. Most of the customers use ETL technologies for their migration projects and thus the problems encountered are very similar to the ones we see in data warehousing patterns.
Data migration can be quite complex for various reasons:
The source and target are most likely heterogeneous and thus data models will be very different
Customers take migration as an opportunity to re-factor their current systems. However, this re-factoring often causes additional cost with additional time, effort and unexpected complexities.
Getting alignment and time commitment from all stakeholders, impacted by the migration process.
It is no wonder that few stats from Bloor Research suggest the following:
84% of data migration projects fail to meet expectations.
37% of the projects exceed the original budget by ~30%.
67% are not delivered on time.
For more click <a href=\"https://www.datagaps.com/blog/etl-validator-for-data-migration-testing/\">Data Migration Testing</a>
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