Data migration is the structured process of extracting data from legacy systems, cleansing it, mapping it to NetSuite's data model, transforming and deduplicating it, validating it, and loading it into the new environment.
It represents a significant point of project risk in any ERP deployment. Messy, unorganized, or incorrectly mapped data can corrupt record relationships, break automated workflows, and compromise financial reporting accuracy from day one.
Decisions regarding the historical cutover (1 year vs. 3 years vs. 5 years, etc.) and scope (transaction details vs. Trial Balances, inclusion of CRM data, etc.)
Legacy data extraction and application of techniques to ensure formatting consistency, duplicate removal, and field standardization.
Mapping legacy data fields with standard and custom NetSuite schemas and documentation of field rules and data types.
Executing sequence-based data loads with multi-level validations and error log analyses.
Final data freeze in legacy systems and loading to production.
End-to-end data validations and audit-ready signoffs.
Novelance approaches data migration with the strict discipline of a financial and data audit. We assign data ownership to people who use the data, not just IT. Every step is documented to ensure data accuracy and completeness.
Organizations undergoing an ERP transition that cannot afford to risk their financial integrity, operational continuity, or reporting accuracy.
Companies with complex data footprints, and multi-entity structures, that need a highly structured, strategic approach to historical cutover
Businesses that need help to migrate years of transactional data, critical CRM activities and essential business and contract files and artifacts.
Data migration is one of the most failure-prone workstreams in any ERP deployment — poorly mapped data can corrupt records, break workflows, and compromise reporting from day one. Clients engage us precisely because they want a specialist on this high-risk work.
The data migration process uses a strict extraction, transformation, and loading (ETL) framework. Data ownership is assigned directly to the business units, and legacy records are cleansed and standardized before loading. Using NetSuite's native CSV Import tools, data is imported through multiple iterative test cycles in sandbox environments to validate mapping rules and reconcile ledger balances before the final production cutover.
Data migration activities are initiated in the first weeks of the project, with legacy data extraction and cleansing running in parallel with requirements discovery. This proactive approach allows developers to run multiple trial data loads in sandbox environments, ensuring that any formatting or mapping issues are resolved long before the final cutover.
Data migration is treated as a primary workstream, not an afterthought. Poor data migration is one of the most frequently cited reasons NetSuite implementations fail, so we begin data profiling, cleansing, and mapping at the start of discovery rather than near cutover. We migrate only the data that earns its place in the new system, validate it through structured reconciliation, and rehearse cutover in a controlled environment before Go-live.