Micromerce Blog

Successful Data Migration: Best Practices for Effectively Migrating Your Data

Data migration is essential for modernizing IT systems, consolidating data centers, and implementing new applications. It encompasses various types, including storage migration, database migration, application migration, cloud migration, and business process migration. Challenges such as data quality, system compatibility, and security can be overcome through careful planning, the use of automation tools, and continuous monitoring. Micromerce provides comprehensive support with a powerful migration platform, proven processes, and extensive experience from over 3,000 successful projects. Companies benefit from transparent insights and efficient solutions, especially in complex migration scenarios such as mergers and acquisitions.

CRM data migration: why accounting is the hardest part

In a CRM data migration the effort does not sit with contacts and companies. It sits with the commercial records: invoices, payments, credit notes, open items and contracts. These records carry a history that may be neither altered nor shortened, and their correctness is verifiable against a single number, the balance. Nobody notices a wrong address. Everybody notices a wrong balance.

Data migration risks in a regulated environment

The main data migration risks in a regulated environment are not volume or technology. They are the burden of proof: for every migrated record it must later be traceable which source it came from, which rule changed it, and who approved that. This shifts effort out of development and into documentation and coordination, typically at a ratio of two to one against a comparable project outside regulation.

Data onboarding: build an interface or exchange files?

The first decision in data onboarding is not file versus API. It is where the data lands: in a folder that waits for a script, or directly in a system that validates the delivery and starts the processing on arrival. We build for the second. The transport can be an upload, an SFTP delivery or an API call, depending on what the counterparty can do. Real time is an add-on, and an expensive one, so the benefit has to be checked before the complexity is bought.

A data migration plan that survives the second run

A data migration plan proves its worth in the pilot, and the pilot’s job is to test the conditions the scale-up will run under: the same process, the same tooling, the same rails as the full migration, only against a smaller slice. Learning is the deliverable, so the setup decides before the first run which result would change the plan: a run time above X, an error rate above Y, running costs above Z. A pilot built as a special case, or meant only to show that "it works in principle", teaches nothing about the scale-up and still costs six weeks.

Data migration testing with anonymized data: keep the structure

Anonymization is a fixed part of how we test data migrations: test data must carry no PII and no PCI data, and it still has to keep the structure of the real dataset, so that anyone can work with it and build transformations against it. The failure mode is not anonymizing too much or too little. It is anonymizing randomly, replacing values in a way that destroys formats, distributions and relationships, so the test passes and the live run fails.