Master Data Management (MDM) Solution

Master Data Management (MDM) is a business and technology practice that ensures a single, trusted view of core data such as customers, products, suppliers, and locations. It aligns people, processes, and platforms to deliver a unified source of truth across the enterprise.

MDM enhances data quality and consistency, leading to reduced operational errors and faster analytics and AI processes. It also speeds up product launches and improves customer experiences, ultimately driving measurable ROI.

Master data identifies entities like products, customers, and suppliers. Reference data standardizes allowed values, such as countries and currencies. Transactional data records events such as orders and invoices that are tied to master data.

A Golden Record is the most reliable version of a master entity, created by applying matching, merging, and survivorship rules to eliminate duplicates and reconcile attributes. It provides consistent data that powers both analytics and operational systems.

Common MDM styles include registry, consolidation, centralized, and coexistence. Centric helps you choose the right style based on your integration needs, data volume, and change management capabilities.

PIM focuses on managing product information for eCommerce and marketing. In contrast, MDM governs multiple domains, such as customers, vendors, and locations, ensuring data governance across the organization. While they serve different purposes, they often integrate and complement each other.

A CDP (Customer Data Platform) builds real-time customer profiles for use in marketing, while MDM manages governed master data across various domains. MDM feeds the CDP with clean identifiers and attributes, ensuring consistent and accurate customer data.

Data governance sets the framework for roles, policies, standards, and stewardship workflows, while MDM operationalizes these policies by applying data models, rules, and approval processes.

MDM leads to fewer errors, faster time to market, reduced DSO (Days Sales Outstanding), improved regulatory reporting, and better marketing conversion through precise customer segmentation.

DAM (Digital Asset Management) focuses on managing digital assets, like images and videos, while MDM governs core business data entities. When combined with PIM, they help create rich product experiences and streamline omnichannel syndication.

Retail and CPG (Consumer Packaged Goods) need accurate product and supplier data. Manufacturing relies on part and BOM alignment, while oil and gas requires accurate asset and location data. Healthcare focuses on provider and patient identities, and the government prioritizes citizen and program data governance.

Typical MDM domains include product, customer, supplier, location, asset, employee, and reference data, such as codes and taxonomies.

Start with a discovery and assessment phase, defining business objectives, data domains, scope, and KPIs. Centric helps create a phased roadmap, beginning with a high-impact value segment. We will also plan the data model, workflow automation, and integrations.

A focused first release for one domain typically takes 3 to 6 months, depending on data complexity, integrations, and stakeholder readiness. Larger, multi-domain implementations will take longer.

The MDM business case outlines both hard savings (e.g., reduced returns) and soft benefits (e.g., faster onboarding, improved analytics). Key performance indicators (KPIs) include match rate, data quality scores, time to publish, and approval cycle time.

Centric uses Pimcore MDM, integrating it with your ERP, CRM, and commerce stack. Pimcore offers flexible data modeling, workflows, APIs, and scalability for enterprise use, with the most flexible licensing options in the industry.

MDM integrates with headless cms like ERP and CRM systems through APIs, messages, and batch pipelines. It publishes the Golden Record to systems like SAP, Oracle, Microsoft Dynamics, and Salesforce, while also consuming updates for survivorship.

Data stewards ensure data quality, manage matching and merging exceptions, enforce standards, and handle workflows. They play a vital role in maintaining the sustainability of MDM efforts.

MDM enforces validation rules, standardizes data, controls reference data, detects duplicates, and offers enrichment services, ensuring completeness, accuracy, and consistency.

Matching identifies duplicates using deterministic and probabilistic logic, while merging applies survivorship rules to retain the most trusted attributes.

Survivorship refers to the process of determining which data source takes priority for each attribute based on factors like trust scores, recency, and business rules. This ensures the creation of a single, trusted view of your data.

MDM handles complex, multi-level relationships, such as product categories, customer corporate structures, and site-to-asset relationships, ensuring they support reporting and approval processes.

MDM supports multilingual data through locale-specific attributes, translation workflows, and channel-specific formatting, ensuring consistent product content and naming across different languages.

Yes, modern MDM platforms like Pimcore are designed to run on cloud-native stacks, offering elastic storage and computing. Hybrid and on-premise deployment options are also available.

Reference data management governs codes and lists such as units of measure and payment terms. It includes version control and approval processes, ensuring consistency across systems.

Consolidation creates the Golden Record and then publishes it back to systems, while centralized MDM acts as the system of record, handling both authoring and governance from a central hub.

MDM supports compliance by establishing a governed source of identity and attributes, with features like audit trails, retention policies, and consent management. This improves subject access and ensures accurate data correction.

Yes, MDM integrates with PIM and DAM systems to syndicate complete product content across various channels like marketplaces, eCommerce marketing, POS, and print, while ensuring that master attributes remain consistent.

Common integration patterns include event streaming for real-time updates, REST and GraphQL APIs for on-demand access, and secure batch processing for high-volume data loads.

We handle legacy data migration by profiling, cleansing, mapping, and loading historical records. We apply match rules to deduplicate and create cross-reference maps, ensuring legacy IDs remain traceable.

Common pitfalls include unclear ownership, fragmented scope, and lack of data stewardship. Centric avoids these challenges by implementing strong governance, clear operating models, and effective change management processes.

Workflows in MDM are configurable and support governance by managing authoring, enrichment, reviews, and approvals. They also incorporate SLAs and notifications, enabling stewards to manage data quality at scale.

Clean master data improves feature accuracy and identity resolution for analytics, CDP, and data science, which leads to enhanced model performance and better decision-making.

A customer 360 is a unified profile of each customer, with deduplicated identities linked to their interactions, preferences, and entitlements. This profile is then shared with systems like CRM, CDP, and customer service platforms.

MDM helps manufacturers by standardizing part specifications, supplier references, and plant location hierarchies. It accelerates new product introductions while minimizing procurement errors.

MDM helps retailers and eCommerce businesses by synchronizing product attributes, prices, and assortments across all channels. It also speeds up catalog onboarding and improves SEO with consistent product titles and attributes.

An MDM hub requires robust security controls, including role-based access, encryption in transit and at rest, audit logs, and approval gates for sensitive changes. Integration tokens should also be rotated and monitored.

In a coexistence model, operational systems continue creating records, but the MDM hub reconciles and republishes mastered attributes, ensuring all systems converge on a consistent data view.

MDM integrates with PIM and DAM systems, where PIM manages channel-ready content and DAM handles digital assets like images and videos. MDM ensures consistent product identifiers and maintains relationships across systems.

We manage codes and taxonomies using reference data management, which includes versioning, approvals, and impact analysis to prevent breaking downstream systems.

MDM supports real-time use cases by leveraging event streams and low-latency APIs, ensuring channels always have access to the most up-to-date mastered data, without waiting for batch processes.

Important data quality dimensions include completeness, accuracy, consistency, uniqueness, timeliness, and validity, with defined thresholds and alerts for data stewards.

We profile the data to identify stable identifiers, then combine exact and fuzzy match keys such as email, phone numbers, addresses, product codes, and vendor numbers, based on the domain.

Centric provides end-to-end support for MDM implementation, including discovery, data modeling, governance, workflows, integration, and change management. Our approach leverages Pimcore MDM to create a single source of truth that powers ERP, CRM, CDP, and eCommerce, delivering measurable results.