Master Data Management
Implementation
Establish single sources of truth for critical business entities through comprehensive master data management solutions that ensure consistency across your enterprise systems.
Return to HomeImplementation Methodology
Our master data management approach begins with identifying master data domains requiring centralized management. Common domains include customer information, product catalogs, supplier records, and organizational hierarchies. We assess current data distribution across systems and quality issues requiring attention.
We design hierarchies and relationships between entities that reflect business structures and reporting requirements. Matching and merging algorithms consolidate duplicate records from disparate systems, employing both deterministic rules for exact matches and probabilistic methods for fuzzy matching scenarios.
Data quality rules ensure accuracy and completeness of master records. Validation frameworks verify data against business rules before acceptance into the master repository. Workflow systems manage approval processes for data changes, routing requests to appropriate stewards based on organizational policies.
Integration architectures synchronize master data across consuming systems, maintaining consistency while respecting system-specific data requirements. We implement both real-time and batch synchronization patterns depending on latency requirements and system capabilities.
Domain Identification
Analysis of business entities requiring centralized management, assessment of current data quality, and prioritization based on business value.
Matching and Consolidation
Algorithms for identifying duplicate records across systems, merging rules preserving data integrity, and survivorship strategies determining authoritative values.
Quality Management
Validation rules ensuring data accuracy, completeness checks preventing incomplete records, and monitoring frameworks tracking quality metrics over time.
System Integration
Integration patterns synchronizing master data to consuming applications, conflict resolution for concurrent updates, and audit trails documenting changes.
Implementation Outcomes
Data Consistency
Organizations implementing master data management typically observe improved consistency of information across enterprise systems. Single sources of truth reduce discrepancies between applications consuming shared data.
Measured through data quality metrics
Operational Efficiency
Centralized master data maintenance reduces redundant data entry across multiple systems. Teams spend less time reconciling inconsistent information and resolving data quality issues.
Commonly reported by client organizations
Regulatory Compliance
Documented governance processes and audit trails support compliance requirements. Clear data ownership and approval workflows demonstrate proper control over sensitive information.
Supports audit and compliance needs
Technology Platforms
We implement master data management using platforms such as Informatica MDM, IBM InfoSphere Master Data Management, and SAP Master Data Governance. These enterprise solutions provide comprehensive capabilities for data consolidation, quality management, and workflow orchestration.
For organizations requiring cloud-native solutions, we work with platforms including Reltio, Profisee, and Semarchy. Integration frameworks connect MDM systems to source and consuming applications using APIs, message queues, and batch synchronization patterns.
MDM Platforms
Informatica, IBM InfoSphere, SAP MDG, and cloud-native solutions
Data Quality Tools
Validation engines, deduplication software, and enrichment services
Integration Middleware
APIs, message brokers, and ETL tools for system connectivity
Workflow Engines
Approval routing, change management, and stewardship interfaces
Governance Framework
We establish data stewardship roles and responsibilities ensuring ongoing data quality and appropriate decision-making. Governance councils provide oversight for policies, standards, and conflict resolution across data domains.
Stewardship Model
Defined roles for data ownership and quality management
Policy Framework
Standards and procedures governing data management activities
Audit Capabilities
Complete change history and approval documentation
Metrics Tracking
Quality indicators and governance effectiveness measures
Target Organizations
This service suits organizations struggling with inconsistent data across multiple systems or facing challenges maintaining accurate customer, product, or supplier information. Companies with duplicate records requiring consolidation benefit from matching and deduplication capabilities.
Regulated industries requiring clear data lineage and governance documentation find MDM helpful for demonstrating compliance. Organizations planning system consolidations or implementing new enterprise applications often establish master data management to support integration efforts.
Suitable Situations
- Multiple systems containing overlapping master data
- Data quality issues affecting business operations
- Regulatory requirements for data governance
- Enterprise system integration projects
- Organizations seeking single customer view capabilities
Project Phases
Master data management implementations follow structured phases with clear deliverables. We maintain regular communication throughout the project ensuring alignment with organizational priorities and timelines.
Assessment and Design
Domain identification, current state data quality analysis, governance framework design, and platform selection
Duration: 2-3 weeks
Platform Configuration
System setup, matching rule development, quality rule implementation, workflow configuration, and integration development
Duration: 6-8 weeks
Deployment and Training
Initial data load, system testing, steward training, documentation completion, and production cutover
Duration: 2-3 weeks
Establish Data Consistency
Contact us to explore how master data management can support your data quality and governance objectives.
Starting from €6,900
Schedule ConsultationRelated Services
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