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Data Migration is a field that is often overlooked as a simple step between retiring an existing platform and bringing to life a new one. The reality is that we are constantly migrating data between systems, implementing new applications, setting up co-existence scenarios and sharing information in a way that could be thought of as data migration.
The actual task of data migration is a complex one requiring experience and a detailed understanding of the steps to be taken, both in terms of business process and technical implementation. This includes a clear delineation of responsibility between IT and business, since far too often the job of manipulating data is relegated to IT, well outside of their core competency. Enabling the migration requires a team experienced in abstracting the technical details such that the business team can implement their rules for migration without ever writing a single line of code, a task for IT.
This document focuses on technical architecture rather than process. We describe an architecture that we’ve found to be ideal in dozens of large data migration scenarios at organizations ranging from global Fortune 500 companies to local Small Businesses. This architecture is portable between different software toolsets; we’ve implemented it in hand-coded systems as well as open source and best-of-breed ETL/DQ solutions.