Master Data Management System
// Master Data Management System
Digatex AI/ML for Engineering and
Digatex AI/ML for Engineering and
Operational Data Integrity
In the Oil & Gas industry, poor-quality master data can impact everything from procurement to predictive maintenance. Our solution, built on Digatex, uses AI/ML to streamline master data governance across asset classes, materials, and engineering hierarchies.
Business Challenges Addressed
- Duplicate, inconsistent, and incomplete asset records
- Non-standard naming conventions leading to poor analytics
- Manual cleansing processes with high error rates
- Regulatory non-compliance due to missing metadata
Solution Capabilities
- AI-driven classification and taxonomy alignment
- NLP-based data standardization and enrichment
- Intelligent deduplication and match-merging
- Change tracking and version control for audit readiness
- Industry-specific templates for Oil & Gas master data
Integration / Architecture
- Works with SAP MDG, Maximo, Oracle for bidirectional sync
- Cloud-based engine with API-driven orchestration
- Bulk upload and live cleansing capability
Business Benefits
- Over 95% accuracy in master data matching
- Time savings of up to 70% in data onboarding
- Enhanced analytics with clean, structured data
- Improved equipment lifecycle management and compliance
Key Use Cases
- Master data migration for brownfield asset integration
- Material catalogue optimization for global sourcing
- Operational data cleanup for predictive maintenance programs
Highlighters
AI models trained on Oil & Gas-specific taxonomies
Live cleansing engine with smart deduplication logic
