High-Volume Record Set
Approximately 250,000 manufacturing master data records requiring migration.
DATA MIGRATION & INTEGRATIONINFOR-TO-NETSUITE MANUFACTURING SYNC
High-Volume Manufacturing Master Data Migration from Infor to NetSuite
A NetSuite integration solution built to migrate manufacturing master data — Bills of Materials, BOM Routings, and Advanced Manufacturing Routings — from Infor into NetSuite, using an OAuth 2.0-authenticated RESTlet integration and a Python-based data transformation layer.
NetSuite ERPRESTlet IntegrationAdvanced ManufacturingPython Automation
Background & Problem
The Challenge
Migrating 250,000+ manufacturing master data records without breaking NetSuite governance limits.
The client ran core manufacturing operations on Infor, including advanced WMS-driven BOMs, BOM Routings, and Manufacturing Routings. Moving this manufacturing master data to NetSuite meant handling roughly 2.5 lakh (250,000) rows exported from Infor in Excel/CSV format — far beyond what manual entry or a simple one-shot API import could support.
Excel-Based Source Format
Flat Excel/CSV exports needing conversion into structured NetSuite objects.
Governance & Usage Limits
Individual record creation at this volume risked exceeding NetSuite's API and script governance limits.
Redundant Record Structures
Many routing lines shared the same parent BOM, creating an opportunity to consolidate.
Secure System-to-System Auth
The client's Python application needed a secure, token-based way to authenticate against NetSuite.
Reliable Batch Processing
Records needed to process without data loss or duplication on failure/retry.
Objectives
Business Requirements
Core integration architecture and batch processing requirements established for high-volume data migration.
- Establish a secure OAuth 2.0-authenticated connection between the client's Python application and NetSuite via RESTlet.
- Convert Infor's Excel-format exports into structured objects mapped to NetSuite's manufacturing master data records.
- Group related routing lines under a shared parent object where source data was similar, reducing total record volume and object count.
- Implement a queue-based processing architecture to stage and throttle the ~250,000-record load.
- Build a Map/Reduce script to consume the queue and create the corresponding records in NetSuite.
Results & Impact
Business Outcome
Operational improvements and governance-compliant execution achieved through custom NetSuite integration.
Reduced Manual Data Entry
Removed manual creation across a 250,000+ row manufacturing dataset.
Reduced Object & Governance Load
Grouping similar records lowered total object count and eased governance pressure.
Resilient, Repeatable Sync Architecture
Queue-based, Map/Reduce-driven design created a reusable processing pattern for future synchronization requirements.
Improved Data Accuracy
Structured data conversion reduced mapping errors compared with manual entry.
Scalable Migration Framework
Created a reusable pattern that can be adapted for other high-volume manufacturing data migrations.
Technology & Core Expertise
Python Transformation • NetSuite Integration • Advanced Manufacturing Module
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