Manufacturing Data, AI, MDM & Analytics Solutions
Build trusted, connected, and AI-ready manufacturing data foundations across ERP, MES, PLM, SCM, IoT, quality, supplier, asset, and customer systems.
Why Modern Manufacturers Partner with Artha:
- Unify fragmented manufacturing data across enterprise and shop-floor systems
- Improve master data quality across products, suppliers, customers, assets, and materials
- Build governed data pipelines for analytics, automation, and AI
- Accelerate SAP, ERP, PLM, and cloud data modernization
- Improve visibility across operations, quality, supply chain, and energy
Manufacturing Transformation Is Blocked by Fragmented Data
Manufacturers run on complex data ecosystems spanning ERP, MES, PLM, SCM, CRM, IoT sensors, supplier portals, quality systems, finance platforms, and legacy databases. When this data remains fragmented, inconsistent, duplicated, or poorly governed, teams struggle to trust reports, optimize operations, improve quality, predict disruptions, and scale AI initiatives.
Siloed Enterprise & Shop-floor Data
Fragmented databases across ERP, MES, PLM, SCM, CRM, IoT, and quality systems hide operational realities.
Inconsistent Master Records
Duplicate and inconsistent product, material, supplier, customer, and asset records lead to procurement and scheduling errors.
Manual & Delayed Reporting
Slow reporting due to batch-heavy and manual data integration processes delays critical response.
Poor Floor-to-Boardroom Visibility
Limited visibility prevents linking physical shop-floor machinery output directly to enterprise-level financial metrics.
Weak Governance & Ownership
Unclear data ownership and poor stewardship lead to decaying datasets that block modern workflow integrations.
Stalled Analytics & AI Pilots
Advanced analytics and machine learning pilots fail to scale because the training data is untrusted or missing context.
Delayed Supply Chain Decisions
Procurement, logistics, and inventory planning decisions are delayed by incomplete or siloed partner and supplier datasets.
Hidden Quality Issues
Product defect patterns and machine degradation risks are hidden across disconnected plant logs and quality spreadsheets.
A Modern Data Foundation for Intelligent Manufacturing
To achieve Industry 4.0 efficiency, manufacturers require a connected, governed, and quality-controlled pipeline. Our manufacturing framework delivers this across 5 critical layers.
Connect
Integrate ERP, MES, PLM, SCM, CRM, IoT, quality, supplier, finance, and legacy systems using batch, API, CDC, event-driven, and cloud data pipelines.
Govern
Define data ownership, business glossary, lineage, policies, stewardship, auditability, access controls, and governance workflows.
Trust
Improve data quality, validation, standardization, deduplication, reference data, MDM, golden records, and operational data observability.
Analyze
Deliver manufacturing analytics, dashboards, operational intelligence, supplier visibility, quality insights, revenue and cost analytics, and performance KPIs.
Scale AI
Prepare AI-ready data products for predictive maintenance, demand forecasting, quality intelligence, supply chain risk, energy optimization, and GenAI-enabled knowledge access.
Who We Help
Artha aligns operations, supply chain, and data architectures to support the business goals of enterprise manufacturing leaders.
Primary Challenges
Handling legacy systems, high integration complexity, ERP/SAP modernization pressure, cloud migration delays, and compliance/governance gaps.
Artha Solutions
Designing modern enterprise data architectures, preparing migration mappings, validating data quality, and implementing governance rules.
Business Outcomes
Reduced migration risks, modernized ETL architectures, faster time-to-value on cloud integrations, and standardized enterprise schemas.
Primary Challenges
Lack of trust in operational data, inconsistent master records across plants, absence of data stewardship, and slow delivery of analytics.
Artha Solutions
Implementing Master Data Management (MDM) platforms, data quality profiling, lineage mapping, and building model-ready datasets.
Business Outcomes
Higher data trust, golden records across key domains (products, suppliers, assets), clear data ownership, and accelerated AI readiness.
Primary Challenges
Poor visibility across plants, delayed supplier performance tracking, inventory volatility, manual reconciliations, and reactive maintenance.
Artha Solutions
Connecting IoT sensor streams, building inventory optimization dashboards, automating OTIF tracking, and deploying predictive pipelines.
Business Outcomes
Improved OEE metrics, real-time supply chain transparency, lower warehouse carrying costs, and transition to proactive maintenance.
Primary Challenges
Dirty legacy data, duplicated product/material master records, broken BOM mappings, and integration friction post-migration.
Artha Solutions
Pre-migration data profiling, vendor and material deduplication, bill of materials (BOM) harmonization, and post-migration validation.
Business Outcomes
Lower S/4HANA migration overhead, cleaner and optimized system data footprint, and seamless integration between PLM and MES systems.
Manufacturing Solution Pillars
Explore our specialized data engineering, master data governance, analytics, and AI practices custom-built for industrial settings.
Manufacturing Data Solutions
Unify shop-floor telemetry and enterprise ERP systems into secure cloud architectures.
Learn MoreMaster Data Management (MDM)
Create golden records for products, materials, vendors, and assets across plants.
Learn MoreManufacturing Analytics
Monitor overall equipment effectiveness (OEE), scrap, yield, and throughput metrics.
Learn MoreAI-Ready Manufacturing Data
Structure, clean, and catalog sensor logs to scale predictive maintenance ML models.
Learn MoreSupply Chain Intelligence
Track vendor OTIF, carrier transit paths, and demand forecasting inventory buffers.
Learn MoreQuality, Asset & Energy
Combine defect logs, repairs, and shift power bills for integrated optimization audits.
Learn MoreSAP, ERP & PLM Modernization
Clean, map, and validate materials and BOM records to accelerate S/4HANA migrations.
Learn MoreData Governance & Observability
Enforce lineage, material stewards, and pipeline checks to stop dirty data before it reaches dashboards.
Learn MoreManufacturing Use Cases
Explore our full catalog of 20 detailed business-outcome use cases for industrial data projects.
Explore Use CasesMeasurable Strategic Outcomes
Modernizing your manufacturing data architecture drives concrete efficiency and risk mitigation.
Faster Data Access
Instant availability of trusted operational metrics across business lines.
Master Data Accuracy
Golden records that unify materials, vendors, and products across plants.
Reduced Manual Work
Automated pipelines replace spreadsheet gathering and manual reconciliation.
End-to-End Visibility
Real-time transparency across shop floors, warehouses, and suppliers.
High Analytics Adoption
Self-service dashboards built on top of governed, trusted data products.
Mitigated Migration Risks
Data cleaning pre-migration ensures new ERP and cloud platforms launch smoothly.
Manufacturing Proof Points
See how Artha helps industrial enterprises resolve complex fragmentation and build trusted data pipelines.
SAP S/4HANA ERP Cloud Migration with AWS and Talend
Modernized SAP S/4HANA and integrated decades of ERP, JD Edwards, Salesforce, IoT, and analytics data into a scalable cloud foundation with 99% accurate ERP integration.
Real-Time Logistics Analytics and ETL Modernization
Migrated legacy ETL workflows to Qlik Cloud CDC streaming, cutting logistics data latency from over 24 hours to under two minutes and reducing shipping delays.
Dynamic Ingestion Framework (DIF) and MDM Implementation
Centralized, cleansed, and unified manufacturing customer and operational data with DIF and MDM, improving data accuracy, automation, and governance.
Rapid On-Premises Talend Master Data Management Deployment
Implemented rapid Talend MDM for a global workwear brand to clean duplicate records and improve production planning, order responsiveness, and manufacturing alignment.
Frequently Asked Questions
Find answers to common questions about our industrial data governance, MDM, analytics, and AI readiness practices.
Manufacturing data solutions refer to the technologies and frameworks used to integrate, clean, govern, and analyze datasets across shop-floor operations (MES, IoT) and enterprise systems (ERP, PLM, SCM) to optimize production and logistics.
Artha designs cloud data lakehouse architectures, builds robust ETL/ELT pipelines, implements Master Data Management, and establishes data governance policies to replace manual reporting and siloed databases.
MDM establishes a single, trusted "golden record" for critical data domains like materials, suppliers, assets, and products. This prevents duplicate purchasing, improves inventory tracking, and supports smooth ERP migrations.
AI readiness requires structuring data, resolving quality issues, documenting metadata, ensuring lineage, and creating clean, governed "data products" that models can reference safely without compliance risks.
Ready to Build an AI-Ready Manufacturing Data Foundation?
Talk with our senior manufacturing data solutions architects to align your operations, supply chain, and systems.
