MDM Framework – Enterprise Master Data Management Framework

Overview: Coforge MDM Framework establishes a single, trusted, governed view of critical business entities — customers, products, vendors, locations, reference data etc. Master data fragmentation creates inconsistent reporting and compliance gaps. Part of Coforge Data Cosmos™ – the innovation backbone comprising platforms, agents, and services that accelerates execution across every phase of the data lifecycle.

Foundation: • Consulting — MDM strategy and roadmap • Business Stakeholder Alignment — Cross-functional agreement on ownership • MDM Principles & Standards — Enterprise-wide standards

4-Phase MDM Lifecycle:

Phase 1: ASSESS • Profile master data across source systems — identify duplicates, inconsistencies, quality gaps • Discover all sources, consumers, and data flows across the enterprise • Evaluate relationships, hierarchies, cross-system dependencies • Assess MDM maturity and define the business case for consolidation

Phase 2: PLAN • Align stakeholders on MDM vision, objectives, and principles • Map source attributes to target canonical model with transformation rules • Design master data model — entities, attributes, relationships, hierarchies, naming conventions • Select MDM architecture (hub-based, registry, or hybrid) based on domain criticality • Plan stewardship workflows for creation, update, and retirement

Phase 3: INNOVATE • Deploy AI-powered matching and entity resolution via Amazon Bedrock for golden record creation • Introduce ML probabilistic matching alongside deterministic rules for higher merge accuracy • Enable AI-driven enrichment — auto-augment master records with external reference data • Integrate Data Cosmos accelerators like AutoClassifier for automated classification, Agentic DQ Resolver for quality scoring, anomaly detection etc. • Embed intelligent duplicate detection that continuously learns from steward corrections

Phase 4: EXECUTE • Merge and consolidate duplicates into golden master records • Publish golden records via APIs, event-driven feeds, or batch synchronization • Deploy continuous monitoring of master data quality, completeness, consistency • Activate stewardship workflows with approval processes for lifecycle management

Architecture Support: • Hub-Based (Centralized) — Single authoritative source • Registry — Federated model linking records • Hybrid — Combination based on domain criticality

Industry Applications: • Banking — Customer 360 across retail, corporate, wealth. Golden records for KYC/AML. BCBS 239. • Insurance — Policyholder, agent, provider MDM. Merge for accurate premiums. • Travel — Guest/passenger MDM across PMS, CRM, loyalty. GDPR consent. • Healthcare — Enterprise Master Patient Index (EMPI) across Epic, Cerner (EHRs).

Business Benefits: • Single trusted view of critical entities • Automated duplicate detection and golden record creation • Improved regulatory compliance • Scalable hub, registry, and hybrid architecture

Cloud-Native on AWS: Deployed on Amazon EKS. Amazon Redshift for master data warehouse. AWS Glue for ETL. Amazon S3 for staging. Amazon Bedrock for AI-powered entity matching.