Master Data Management (MDM) describes a type of enterprise data management architecture, governed by a collection of formal data quality practices and processes, designed to leverage digital technologies for the entire business.

Getting MDM right represents a critical data management component for your entire enterprise. This article describes MDM’s role in an organization and other data strategies or concepts, a first step towards running successful MDM projects.

What Is MDM And Its Role in An Organization?

Think of MDM as the plumbing in your house, which transports freshwater from a reservoir or well for washing dishes and taking showers. Instead, MDM cycles data from a standardized data hub for your business departments to do tasks like accept payments and market new product lines. Enterprises want good MDM to have the “360-degree view” of business information they need to maintain and grow fully.

Master Data Management originated in the 1990s to deal with lots of disjointed data. For example, schools would find the same student represented in different systems for admission, registration, textbook sales, grading, career counselling, and alumni services. The student would engage with various departments for different needs, each place duplicated the same types of attributes, causing inefficiency and likelihood for error. Schools and other businesses looked to MDM to clean this overlapping raw data for use in any department.

sample1

Before computerized systems, MDM meant setting up, using, and maintaining a folder system in a filing cabinet combined with using interdepartmental mail. For instance, hospital volunteers called candy stripers would physically deliver patient data from one department (e.g., radiology) to another (e.g., a physician’s office filing cabinet). Some of the same data from a patient’s folder in a doctor’s office would go to a nursing station or admissions (usually through some standardized forms). This required workers to sift through paper and wait for information to be delivered.

Today’s MDM’s systems use software and networking advances, people, and data governance processes to get work done more efficiently. Rather than paper, current MDM controls and operates on Master Data and Reference Data explained in the next sections.

Related: Top Ten Master Data Management Benefits

What Is Master Data?

Master data tends to be harder to visualize as it describes core data assets distributed across many different databases, including in the cloud. This associated information belongs to specific entities necessary for a business to operate and grow. Typically, master data breaks down into four domains:

  • Customers
  • Products
  • Locations
  • Other

Each domain can be further divided into subsections:

  • Customers > Company name, address, email, and phone.
  • Products > The good or service in use and the ingredient or part to make it.
  • Location >  The region where the head office is located.
  • Other > Calendar of company events, licenses.

Likewise, these subsections can split into further subcategories.

Any level of master data comprises a single source of truth or golden copy that remains consistent and non-duplicated. The power of master data lies in that it can be copied but not altered in more than one place, a hub.

Hubs containing stored and accessible master data come in different flavors:

  • Registry > checks the MDM hub to correct any contradictions among multiple sources.
  • Consolidated > gathers master data from multiple systems into the hub where it is sourced.
  • Coexisted > records duplicate master data with the master data in the hub and the duplicate in each source system.
  • Transaction-based > enhances the data through algorithms ensuring the data is accessible in the source system.

Keep in mind that master data, in any hub, works only as the MDM governed procedures and processes implemented to clean the data.

What Is Reference Data?

Consider reference data, a type of master data that functions as a “Rosetta Stone” for enterprise and departmental applications to understand and work with one another. Typically, other data in a database or external information needed to do business constitutes reference data.

  • Here are two examples:
    The American Bankers Association (ABA) assigns all financial institutions a routing number. An internal account number uniquely identifies a person’s financial product at a bank. The individual bank assigns it. Both the routing and account numbers are needed to release funds for a cashed check or to deposit.
  • The USPS lists reference data, the state, as pull-down menu values on a form. See below:

USPS

 

 

 

 

 

 

 

 

 

What Is Enterprise Data Management, and How Does MDM Fit Into It?

Sometimes MDM concepts and related terminology get confused with enterprise data management. While MDM and enterprise data management make information more useful throughout the company, they have slightly different meanings.

Enterprise data management describes a “holistic framework comprising the people, processes, and technology that optimizes data from a variety of different sources, then makes it available when and where it’s needed.” Think of Enterprise Data Management as a type of blueprint, like a house. Within enterprise data management, MDM describes a specific platform that reduces transaction costs, integrates data, standardizes critical data, and simplifies data architectures across the company so that the entire business can function.

MDM cannot work alone in Enterprise Data Management without other data management components. See the diagram below.

EDM

Using the house metaphor for enterprise data management provides another way to think of MDM. A building has many different systems besides plumbing. Water gets heated by gas or electricity to provide hot water. Most likely different companies provide gas and water. But you will not get hot water alone. You need the gas for plumbing and the house to be functional.
Likewise, MDM does not work alone within an enterprise data management strategy. MDM requires good data quality and reference data management towards providing master data. The enterprise data architecture and privacy and security require appropriate access and control for master data, and all the other enterprise data. MDM cannot work alone as an enterprise data management solution.

Why is Data Management Important, and Why Does it Include MDM?

Data management covers a broader concept than enterprise data management or MDM. It describes “a comprehensive collection and hierarchy of practices, concepts, procedures, processes, and a wide range of accompanying systems that allow for an organization to gain control of its data resources. This spectrum includes business strategies, database, business intelligence, and MDM, among others. Data management’s importance lies with its tremendous monetary and social value, as the Harvard Business Review puts it.

See below for a birds-eye view of data management, including MDM.

business strategy

 

 

 

 

 

 

In the 2010s, data management’s criticality became particularly pronounced. More significant and frequent data breaches disrupted banks, supermarkets, governments, and a hospital. Also, ransomware has gained traction, with increasing monetary demands and dangers to privacy. Governments recognized the high financial and political outcomes from data. In response, legislation from Europe (the GDPR) and California (the CCPA) order companies to protect an individual’s privacy. Companies and individuals recognize that they need data management to prevent fines and mishaps and to take advantage of new opportunities, like machine learning

MDM describes one type of data management architecture designed to connect many different data sources, easier. Since MDM keeps shared data standardized according to Master Data Governance, data is better controlled and more accessible. As a result, MDM gives companies a huge advantage to use all sorts of technologies and process improvements quickly. The data management diagram below shows MDM from this perspective

digital transformation

What is Master Data Governance (MDG)?

In the previous sections of this article, data governance overarches all different enterprise data management and data management components, gluing a collection of formal practices and processes together among different data management components. Master Data Governance (MDG) describes a specific area designed to guide MDM.

MDG covers details about:

  • Who > The organizational roles and responsibilities for entering, maintaining, using, archiving, transforming, and deleting master and reference data.
  • What > The content and documentation about master data, reference data, and the technical system managing the master data.
  • Why > The purpose of using master and reference data, as defined by the business and data strategies (See the diagram from Global Data Strategies, above).
  • Where > technology platform needed to store, clean, and standardize master data.
  • How > The assessments and actions needed to keep master and reference data beneficial as the organization changes over time.

Master Data Governance complements and interacts with other corporate Data Governance areas. Again, applying a water governance perspective to our model of a house plumbing system makes a good analogy. Plumbing and water transportation follow different requirements by the utility company to get water to the house. Federal, state, city, and town entities and regulations determine what can go into the water (like fluoridation), who monitors and manages that water, and water resource conservation. These processes and activities form water governance and manage different aspects to manage water. See the wheel below.

OECD Water Goverance diagram

Just as water needs to be governed, so does data. DAMA, a professional organization, created the DMBOK wheel to illustrate the processes and activities forming data governance needed to keep different data management entities together.

DMBOK Wheel

Notice, in the DMBOK Wheel, that MDG connects the corporate data governance with reference and master data. Also, MDG relies on other data management components, such as security and data quality, to be managed well. MDG may touch on types of data governance for the MDM platform to work well. But all the other pieces like security must be in place, from the hardware to worker training. Securing MDM does no good if an employee leaves a flash drive or laptop vulnerable or shares the account password. All corporate governance areas, including MDG, need to be considered.

Future blogs will explore each of these components with MDM.

Conclusion:

Master Data Management (MDM) enables your business to take advantage of digital technologies to administrate better, provide goods and services, handle logistics, and deliver excellent customer service. MDM describes a smaller component of enterprise data management and data management. Other data management strategies and areas also need to be considered.

Corporate data governance glues all data management areas together. MDG represents one type of data governance standardizing actions among people, technology, and operations, to keep master data, including reference data, useful. Enterprises, industries, geographical areas, and internal business and cultural norms make up MDG. An organization needs to follow this MDG guidance before, while, and after implementing MDM platforms and programs.

Learn More About MDM:

Websites:

Organizations and Associations:

Videos:

  • Master Data Management: Aligning Data, Process, and Governance by DATAVERSITY.
  • Enterprise Data Management: What does good like? by DAMA Australia.
  • Seven Data Governance for Master Data Management by Lights OnData.

Learn More About WinPure MDM Tool

Last Updated on 31st March 2021 by admin

By Michelle Knight | November 17th, 2020 | Posted in Master Data Management (MDM)

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