Dynamics GP to NetSuite Data Migration
Choosing NetSuite over Dynamics 365? Mine automates the mapping between GP's Dexterity-based schema and NetSuite's cloud-native entity model — translating cryptic table names, restructuring charts of accounts, and handling ISV data.
Working with enterprise teams on active migration programs
4–8 weeks
to production-ready mappings
40–50%
cost reduction vs. manual migration
90%+
average mapping confidence
Most enterprise migrations start 6+ months behind schedule. Yours doesn't have to.
This guide is for VPs of IT, data architects, and migration leads at companies moving data from Microsoft Dynamics GP to NetSuite — whether you're scoping, planning, or mid-program.
Dynamics GP uses a proprietary Dexterity-based SQL Server schema with non-descriptive table names — RM00101 for customers, PM00200 for vendors, GL00100 for accounts — while NetSuite uses a modern cloud-native entity model with intuitive record types. Mine translates GP's legacy naming conventions and flat table structures into NetSuite's subsidiary-based dimensional model automatically.
Based on enterprise migration programs led by Mine's founding team
Last updated March 2026
How Mine automates your Microsoft Dynamics GP to NetSuite migration
Mine auto-maps GP's cryptic table names (RM00101, PM00200, GL00100) to their NetSuite entity equivalents — including GP's obscure column names like CUSTNMBR, VENDORID, and ACTINDX.
GP's flat chart of accounts is analyzed and decomposed into NetSuite's dimensional model — accounts, departments, classes, and locations mapped based on actual GL posting patterns.
ISV module tables are profiled alongside GP core tables and flagged separately — Mekorma, Binary Stream, and SalesPad data is cataloged with migration vs. archive recommendations.
GP's work/open/history table split is unified into NetSuite's single transaction model with proper period assignments and status translations.
Get your Microsoft Dynamics GP to NetSuite mapping analysis — see results in under an hour
Migration timeline: manual vs. Mine
Traditional approach
Timeline
6–10 months
Estimated cost
$300K–1.2M
Team size
4–8 consultants
Typically requires
×Manual field mapping in spreadsheets
×Custom ABAP/SQL extraction scripts
×3–5 mock migration cycles
×Dedicated source system consultants
×Manual reconciliation testing
With Mine
Enterprise benchmarksTimeline
4–8 weeks
Team size
1–2 internal resources
Estimated cost
40–50% less
Included
✓Schema profiling & analysis
✓AI-generated field mappings
✓Transformation SQL
✓Validation & readiness reports
✓Production-ready load files
Common challenges migrating from Microsoft Dynamics GP to NetSuite
GP's Dexterity table names to NetSuite entities
GP uses non-descriptive table names inherited from its Dexterity framework — RM00101 (Customer Master), PM00200 (Vendor Master), GL00100 (Account Master), IV00101 (Item Master). NetSuite uses intuitive entity names. Building a complete crosswalk across hundreds of GP tables requires deep knowledge of GP's undocumented schema.
Explore related migrations →Flat chart of accounts to NetSuite dimensional model
GP uses a flat or minimally segmented chart of accounts. NetSuite uses a multi-dimensional structure with subsidiaries, departments, classes, and locations. Decomposing GP's account structure into NetSuite's dimensional model — and deciding which GP segments become which NetSuite dimensions — requires analysis of actual GL posting patterns.
Explore related migrations →ISV and third-party module data
Most GP installations include third-party ISV modules (Mekorma for payments, Binary Stream for multi-entity, SalesPad for order management) that store data in custom SQL tables. These have no NetSuite equivalent and require individual analysis to determine migration scope vs. archive vs. rebuild.
Explore related migrations →Work/Open/History table split
GP stores transactions across separate work, open, and history tables (SOP10100 for sales work, SOP30200 for sales history; GL20000 for open year, GL30000 for GL history). NetSuite uses a unified transaction model. Deciding how much history to migrate and unifying GP's split tables requires careful cutover planning.
Explore related migrations →Microsoft Dynamics GP to NetSuite field mapping — what data moves
10 data objects typically migrated
| Source Object | → | Target Object |
|---|---|---|
| RM00101 (Customer Master) | → | Customer |
| PM00200 (Vendor Master) | → | Vendor |
| GL00100 (Account Master) | → | Account + Dimensions |
| GL20000/GL30000 (GL Trans) | → | Journal Entry |
| IV00101/IV00102 (Items) | → | Item |
| SOP10100/SOP30200 (Sales) | → | Sales Order / Invoice |
| POP10100/POP30100 (PO) | → | Purchase Order |
| RM20101 (AR Open) | → | Invoice (open) |
| PM20000 (AP Open) | → | Vendor Bill (open) |
| UPR00100 (Employees) | → | Employee |
Typical enterprise migrations include 500K–10M+ records across these objects. Mine handles profiling and mapping at any scale.
The cost of manual Microsoft Dynamics GP to NetSuite migration
Companies typically manage this migration during their NetSuite implementation using CSV exports from GP's SQL database. The table name translation, chart of accounts restructuring, and ISV data handling are largely manual — adding weeks to the implementation timeline.
Frequently asked questions
Related migration paths
In one enterprise migration, a single field mapping error in customer master data caused $100K in billing discrepancies that went undetected for 6 months.
Mine catches these issues before they reach production.
Built by a team that led SAP, Oracle, and Salesforce data migration programs for Fortune 500 companies at a Big 4 consulting firm. Currently in design partnership with enterprise clients running active migration programs.
Ready to migrate from Microsoft Dynamics GP to NetSuite?
Tell us about your migration and we'll show you how Mine can help.
No commitment required. We'll review your migration scope and share a preliminary assessment within 48 hours.
You'll receive a preliminary mapping analysis showing how your source objects map to your target schema, with confidence scores and flagged risk areas.