What Is Master Data Management (MDM)?
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Talk to our experts- Master data management (MDM)
- Master data management (MDM) is the discipline of keeping an organization's shared master data, the core records about customers, products, suppliers and locations, uniform, accurate and governed across every system that uses them. Business and IT work on it together, sharing responsibility for the stewardship, governance and accountability of those records.
Also called: MDM
How it works
Gartner defines master data as the least number of consistent and uniform sets of identifiers and extended attributes that describe the core entities of an enterprise and are used across multiple business processes. The most commonly found categories are parties (customers, suppliers, employees), products, financial structures such as ledgers and cost centers, and locations.
Master data is different from the data around it:
- Master data describes the business entities that give context to transactions: the customer, the item, the ship-to location.
- Transactional data records business events, such as orders and receipts.
- Reference data classifies and categorizes rather than describing entities.
MDM provides the processes that keep master data in shape: collecting, aggregating, matching, consolidating, quality-assuring, storing and distributing it across the organization. Processes commonly seen in MDM also include item master creation, product codification, data enrichment and hierarchy management.
How master data moves between systems
Three ways master data can be collated and distributed to other systems:
- Consolidation: master data is captured from several sources into a single hub, then replicated to other systems.
- Federation: a single virtual view of master data is provided from one or more sources to one or more destination systems.
- Propagation: master data is copied from one system to another, typically through point-to-point interfaces in legacy setups.
Example
A distributor runs an ERP, a PIM and a Shopify store, and sells 2,000 items. If all three systems can edit every product field, each field has 3 copies across 2,000 items, or 6,000 values that can drift apart. A buyer sees one weight on the website, the warehouse ships against another, and nobody knows which is right.
With MDM, the distributor writes down who owns what. The ERP owns item number, cost, weight and stock. The PIM owns long descriptions, specs and images. Shopify receives both and is never edited directly for those fields. Each value now has one place where it is changed, and every other system copies from there.
On Shopify
In Shopify, metafields extend data models such as products, customers and orders with your own fields, and metafield values can be added to products or variants. Shopify's ID metafield type is meant to store the identifier of a resource in another system, so a product can carry, for example, its item number from the ERP. Metafield definitions enforce validation rules so values stay consistent and reliable.
For bulk changes, Shopify supports the bulk editor and CSV import. A common pattern is for an integration to keep Shopify in step with the system that owns each field, rather than staff editing the same data twice.
How Uncap helps
Uncap's guide to PIM platforms for Shopify lays out the B2B pattern: product master data originates in the ERP (part numbers, bills of materials, inventory classification, customer pricing tiers). The PIM enriches that raw data with content, governs its quality and publishes the right version to each channel. The guide calls that three-layer stack, ERP to PIM to Shopify, the foundation of a clean B2B product data operation.
Sources
Frequently asked questions
What is MDM in simple words?
It is keeping one consistent, accurate version of your core records, such as customers, products and suppliers, with clear stewardship and accountability, so every system works from the same data instead of its own siloed copy.
Why is master data management important?
It keeps an organization's critical data consistent and accurate across all systems, which reduces the discrepancies and errors caused by multiple, siloed copies of the same data.
What are the key components of master data management?
Gartner's definition names business and IT working together on stewardship, governance and accountability for shared master data. The processes commonly named include collecting, matching, consolidating, quality-assuring, storing and distributing that data.
