MDM 101: A Simple Explanation of Master Data Management

Managing master data refers to organizing and storing core data to improve its consistency and quality across business processes. Maintaining a system of record can help ensure that errors within one application do not spread to the entirety of your company’s data sources. In addition to operational efficiency, a master data management program can help you improve your data quality.

What is master data?

Master data is the core data that business processes use. It is a consistent set of identifiers and attributes that describe the essential entities of an enterprise. Master data encompasses and describes other types of data like transactional data and customer data. In other words, master data provides the context that makes other data useful to analytics. It is the single source of truth that all other systems that generate and store data can refer back to. Without master data management, there is no concise way to compare and share data between systems.

Why is master data management important?

Most modern businesses utilize several different platforms and applications. For example, retail companies commonly have an app for rewards points accumulation or to track shipping. In addition to this application, they likely have a POS system that can pull customer data for in-store purchases. Each of these platforms needs to be able to communicate and compare data to avoid inconsistencies or redundancies.

Businesses and organizations generate tons of data every day. Harnessing the power of this data can provide business owners and employees with the context they need to make sense of trends and changes in data. Improving upon workflows and ensuring vigilant data governance are both essential benefits of data management.

What types of data will be managed?

There are several different types of data, all of which, when properly managed, can be used by stakeholders and employees to fuel company success. A few of the most important types of data a business will encounter include:

  • Hierarchical data
  • Metadata
  • Transactional Data

Hierarchical Data

Hierarchical data plays a significant role in our understanding of data sets because it identifies causal relationships. For example, suppose you recently made changes to your ad campaign. Shortly after making these changes, you may have noticed a drop off in sales, despite it typically being your busy season. Hierarchical data is the data that explains the relationship between the dip in your sales and the change to your ad campaign.


Metadata is often referred to as “data about data.” While this namesake is an oversimplification, it does an excellent job of explaining metadata’s role in master data management. As mentioned above, companies generate tons of data every day. Rather than sifting through all this data ourselves, we often look to metadata. Metadata provides context about data, like where it originated and how it is related to other data. You will not know the exact details of the data, but you will know enough about it to understand its significance.

Transactional Data

This type of data is created any time a transaction occurs. It differs from other kinds of data in that it relates to worldly affairs directly. In other words, transactional data are unit-level exchanges. Invoices, ticket stubs, and sales are all forms of transactional data.

The above-mentioned data types are not an exhaustive list. Data is a vast and nearly limitless resource. For this reason, it can be challenging to keep track of every kind of data without a master data management system. It is integral for your data sets to communicate and make sense of each other so that your company can turn findings into valuable and actionable insight. If you have questions regarding what master data management can do for your business, reach out to an industry leader in data science software, like TIBCO.

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