At Masterdata, we understand the importance of having accurate and reliable data to drive your business. That’s why we’re excited to bring you the ultimate guide to Master Data Management (MDM) – a comprehensive resource that will help you get the most out of your data.
One of the most commonly asked questions at our DAMA events is, “What is master data management?”
Clearly, there is some confusion out there.
- Various definitions of Master Data Management
- Why is Master Data Management important?
- How does Master Data Management work?
Let’s start with the obvious: Master Data Management (MDM) is not the same as Mobile Device Management (MDM)
Various definitions of Master Data Management
Various sources define master data management in various ways, for example:
“Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets”
Gartner
“MDM is the practice of defining and maintaining consistent definitions of business entities, then sharing them via integration techniques across multiple IT systems within an enterprise and sometimes beyond to partnering companies or customers”
Philip Russom, TDWI
Master data management (MDM) refers to the practice of aggregating all an organization’s critical business entity data (e.g. customer, product, supplier) into one master reference source. As a single point of reference, a properly compiled and governed MDM reference functions as the most consistent and uniform data source.
Precisely
Bringing these together, we define Master Data Management as a process that involves the management of critical data assets to ensure uniformity, accuracy, stewardship, semantic consistency, and accountability across an organization. MDM aims to create a “single source of truth” for important data, such as customer information, product data, and financial data.
This definition shifts away from the outdated notion that MDM is a technology, to reflect the reality that master data management is a business capability.
What is Master Data?
Master data are the objects in a business that provide context for transactions.
For example, for a procurement transaction a supplier (person) may provide a service (thing) under the terms of a contract (concept). For a purchase, a customer (person) may buy a product (thing) from a store (place).
To better understand this concept, it’s important to contrast master data with other categories of business data.
Reference data are a subset of master data, such as country lists or customer categories, that are used to categorise and classify data.
Transactional data, such as sales orders, payments, or insurance claims, is data generated by business applications while supporting daily operations, while analytical data is data created through calculations and analysis of transactional data to provide higher-level insights.
In contrast, master data is data on the business entities that systems reference to complete transactions. Analytical data is often used to provide a deeper view of master data objects.
Master data is not a concept – it is data we use every day to reflect our business dealing. Our customers, our suppliers, our staff, our products, our branches, our depots, and many more.
Customer data is a go-to example of master data, since every organization considers customer data to be master data. Up-to-date customer data is essential to maintain business continuity and avoid missed opportunities. Other examples of master data include product information, location information, and financial structures such as ledgers and cost centers.
Why is Master Data Management important?
In today’s data-driven business environment, it’s essential to have high-quality data that can be trusted. Poor data quality can lead to inefficiencies, increased costs, and missed opportunities. Through MDM, businesses centralise their data management efforts, ensuring that critical data is accurate, up-to-date, and accessible to everyone who needs it.
How does Master Data Management work?
MDM involves a series of processes, enabled by technology, that work together to create a single source of truth for critical data. The process typically involves identifying key data assets, cleansing and standardizing data, and creating a master record that can be used across the organization.
Data Management prerequisites for Master Data Management include:
- Data Governance: The process of defining and managing policies, procedures, and standards for managing master data.
- Data Quality: The process of ensuring that master data is accurate, complete, and unique.
- Data Modelling and Metadata: The process of designing data structures that enable efficient data management, and agreeing on business context
- Data Security: The process of ensuring that sensitive master data is not inappropriately accessed
- Data Integration: The process of combining data from multiple sources into a single, unified view.
Why the confusion?
A lot of the confusion has been created by vendors touting different technology solutions, with very different foundations, as being master data management. What is the difference, for example, between Master Data Management and Customer Relationship Management, or a PIM and CMS?
Another source of confusion is that master data is often referred to as the “golden record” or “single view of the truth“. Older MDM solutions were limited to a single domain, such as customer or product, and vendors promoted these seperate products as master data.
When you embark on MDM, make sure the reason you do this is to align master entities to a system of engagement defined by the business. Do not feel you have to get to one version of the truth.
Michelle Goetz, Forrester Research
Different technical architectures also confuse the issue. Most commercial MDM solutions are based on the concept of a centralised hub ( a new database) which is intended to hold and distribute the master record. However, an opposing solution uses the concept of a messaging bus, or data virtualisation engine, that distributes data without creating a new database or hub. In this case, the model uses existing sources to build a complete record.
More recently, modern MDM platforms leverage graph technology which improve their ability to understand relationships between and across entities. These 4th-generation systems deliver very different insights to older platforms.
The bulk of the confusion comes from this focus on technology. Technology should be the last consideration when planning for MDM.
In master data management, fundamentally, your data problems are not technology problems. They are not even MDM problems. Your data problems aren’t even really well … data problems. They are business problems.
Stephen J. Smith, Eckerson Group
When you see master data management as a business change – including people, process, technology and data – to enable a business goal then hopefully what it means to you, and why it is important, will be clear.
Data Quality Matters 
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