Master Data Management

What it is, how it's implemented and why it matters

By David Loshin

Today, as more information is shared among colleagues and partners, everyone’s connectedness is enhanced. Not only do systems work better together, but the people managing those systems forge better working relationships, which lead to more effective business management and, ultimately, to competitive advantage. Yet, as we continue to share more information, it has become clear that years of siloed application and information architectures have led to “islands of information coherence.”

Traditionally, data architectures have been designed to support individual business application areas with definitions, dictionaries, structures and more – all defined from the aspect of each application. The result? Multiple unconnected, and often disparate, sets of data intended to represent the same business concepts are sprinkled throughout the enterprise.

To better exploit data across the enterprise, however, organizations need integrated data, clearly defined business concepts and an understanding of how those concepts are represented within the company’s data stores. Master data management (MDM) offers a solution for integrating, managing and sharing information through a set of methods and techniques that help organizational teams collaborate to synchronize their data.

What is master data?
Master data objects are those “things” that we care about – the things that are logged in our transaction systems, measured and reported on in our reporting systems, and analyzed in our analytical systems. Common examples of master data include customers, suppliers, parts, assets, products, locations and contact mechanisms.

Consider the following transaction: “David Loshin purchased seat 15B on flight 238 from BWI to SFO on July 20, 2006.” Table 1 shows some of the master data elements and their types in this example.

Table 1: Master data elements 

Master data tends to exist in more than one business area within the organization – so the same customer may show up in the sales system and the billing system – but the master data tends to be relatively static and does not change frequently.

Master data objects may be classified within a hierarchy – but hierarchies can become complex pretty quickly. For example, we may have a master data category of party, which in turn consists of individuals or organizations. Those parties may also be classified based on their roles, such as prospect, customer, supplier, vendor or employee. Although we may see a natural hierarchy across one dimension, the taxonomies applied to the data instances may actually cross multiple hierarchies. For example, a party could simultaneously be an individual, a customer and an employee.

What is master data management?
Master data management is a program composed of the business applications, methods and tools that implement the policies, procedures and infrastructure to support the capture, integration and subsequent shared use of accurate, timely, consistent and complete master data. Among other things, an MDM program is intended to:

• Assess the use of core information objects, data value domains and business rules in the range of applications across the enterprise.
• Identify core information objects relevant to business success used in different application data sets that would benefit from centralization.
• Instantiate a standardized model to manage those key information objects in a shared repository.
• Manage collected and discovered metadata as an accessible, browsable resource and use it to facilitate consolidation.
• Collect and harmonize unique instances to populate the shared repository.
• Integrate the harmonized view of data object instances with existing and newly developed business applications via a service-oriented approach.
• Institute the proper data governance policies and procedures at the corporate or organizational level to ensure the continuous maintenance of the master data repository.

How is MDM put into practice?
There are three basic approaches to implementing an MDM application:

• The registry.
• The master repository.
• The transaction hub.

In the registry model, a master index is created with a unique identifier assigned to each managed entity, such as person or product. The registry maintains links to all locations across the enterprise where there is a record for that entity, and it manages a link between the master identifier and the target system’s local identifier for each entity. In the registry model, the master data is distributed across the enterprise, but master records can be materialized as needed.

In the master repository, for each master object, a set of core attributes associated with each master data model is defined and managed within a single master system. The master repository is the source for managing these core master data objects, which are subsequently published to the application systems. In some instances, within each dependent system, application-specific attributes can be managed locally, but they are linked back to the master instance via a shared global primary key. In this approach, new data instances may be created in each application, but those newly created records must be synchronized with the central system.

In the transaction hub, a single repository is used to manage the core master system, and data is not replicated to other systems. Applications request information from the central hub and provide updates to the central hub. Because there is only one copy, all applications are modified to interact directly with the hub.

Master data management is more than just an application – it is a composition of tools, methods and policies that will help you exploit the value of corporate information and turn data into a competitive asset. The secrets to success lie in understanding how MDM will transform your organization into one with a strong data governance framework, articulating the roles and responsibilities for data stewardship and accountability, and creating a culture of proactive data quality assurance. Consider how moving to the different target architectures will affect the way you do business and prepare your organization for the rapid change.

A successful master data management implementation will lead to more effective integration of business and technology, better organizational collaboration and productivity, ultimately resulting in increased competitive advantage.

Bio: David Loshin, a widely recognized expert in information quality, is President of Knowledge Integrity Inc., an information management solution company.