Create Trusted Master Data for Products, Suppliers, Customers, Materials, and Assets
Artha helps manufacturers standardize, govern, deduplicate, and manage critical master data domains so analytics, ERP modernization, supply chain, operations, and AI initiatives run on trusted data.
Modern Solution Brief
Manufacturing depends on high-quality product, material, supplier, customer, asset, plant, and reference data. Siloed operations and disparate plants lead to duplicate records, mismatched bills of materials (BOM), and broken procurement cycles. Implementing Master Data Management (MDM) resolves these data quality issues, ensuring every plant, vendor, and part is mapped to a single golden record.
Master Data Domains Managed
Standardizing core entities across plants, warehouses, and partner channels.
Product Master
Unify specifications, drawings, and metadata across PLM, ERP, and catalogs.
Material Master
Clean and deduplicate raw materials, components, and packaging parts to optimize procurement.
Supplier / Vendor Master
Establish a unified vendor profile across locations to track spend, contracts, and performance.
Customer Master
Harmonize distributor and end-user profiles to improve sales coordination and service.
Asset & Equipment Master
Track machinery, parts lists, and plant tag details to build predictive maintenance plans.
Plant & Reference Data
Standardize units of measure, plant codes, and cost centers across global facilities.
Technical & Platform Capabilities
Engineered processes built to align physical inputs with executive data structures.
Data Profiling & Quality Rules
Assess data errors, identify anomalies, and enforce formatting rules.
Match & Merge Logic
Configure rules to automatically group duplicate records and resolve conflicts.
Stewardship Workflows
Define approval processes for data stewards to manage and enrich golden records.
Hierarchy Management
Track relationships between assemblies, parts, components, and product structures.
AI-Assisted Operations and Governance
Automate deduplication, classification, and anomalies checks with human stewardship oversight.
AI-assisted Duplicate Detection
Machine learning models classify spelling errors and identify matching parts.
Attribute Classification
AI analyzes raw descriptions to suggest missing fields, materials, or category tags.
Anomaly and Drift Alerts
Detect schema changes or data entry drift before errors affect downstream systems.
Frequently Asked Questions
Get answers to questions regarding this solution area.
Legacy ERP systems, independent plant databases, and manual data entries generate duplicate records over time. Different names for the same vendor or component lead to inventory double-ordering and reporting inaccuracies.
Cleaning, deduplicating, and mapping materials and suppliers BEFORE migrating to S/4HANA or other modern cloud ERP systems prevents transferring dirty data, reducing migration delays and risks.
Ready to Begin?
Connect with our data integration and enterprise platform specialists to scope your project.
