What is Master Data? Master Data Types Explained

By FX Nicolas, Chief Product Officer at Semarchy

Last updated September 12, 2025

Master Data Management is simple…once you have the big picture!

This post provides:

• An overview of the classification of data, describes the types of master data (reporting, transactional, master, reference, and metadata)
• An explanation of how master data types impact business decisions.
• An explanation of why master and reference data have a critical position in this organization.

There are different categories of data

The following data classification is commonly agreed upon in the data management field:

• Transactional data
• Master data
• Reporting data
• Metadata
• Big data
• Unstructured data

Let’s have a look at these various data categories.

What is transactional data?

Transactional data describe business events and represent the largest volume of data in the enterprise. Examples of such events include:

• buying products from suppliers
• selling products to customers
• shipping items to customer sites
• hiring employees
• managing their vacations
• changing their positions

You manage transactional data every day – they make the enterprise world spin. Transactional data is typically handled in operational applications such as CRM, ERP, SCM, HR, and others. It can be very detailed and forms the foundation of many analytical processes, offering valuable insights into customer behavior, business operations, and revenue streams.

In addition, transactional data is referenced and shared by several systems, with much of the associated reference data relating to concepts that impact business processes (e.g., order status such as CREATED, APPROVED, REJECTED) or providing standardized semantics that clarify the interpretation of a data record (e.g., employee job position such as JUNIOR, SENIOR, VP).

Some reference data can be universal or standardized (e.g., Countries – ISO 3166-1), while others may be agreed upon within the enterprise (customer status) or a given business domain (product classifications). Reference data management software supports this by providing essential standards and rules to ensure data consistency and accuracy throughout the organization, facilitating data integration and interoperability through a unified classification framework.

What is master data?

Master data is key business information that supports the transactions. It describes the customers, products, parts, employees, materials, suppliers, and sites involved in the transactions. It is commonly referred to as Places (locations, geography, sites), Parties (persons, customers, suppliers, employees), and Things (products, items, materials, vehicles).

Master data already exists and is used in the operational systems, with some issues. Master data in these systems is:

• • Not high quality data,

• • Scattered and duplicated;

• • Not truly managed. 

Master Data is usually authored and used by existing business processes in the normal course of operations. Unfortunately, these operational business processes are tailored for an “application-specific” use case of this master data and, therefore, fail in achieving the overall enterprise requirement that mandates commonly used master data across applications with high-quality standards and shared governance.

What is reporting data?

Reporting data is, in a nutshell, data organized for the purpose of reporting and business intelligence. Data for operational reporting, as well as data for enterprise (highly aggregated) reporting, belong in this category.

Reporting data is created from transactional data, master data, and master reference data. It offers stakeholders valuable insights into business performance, operational efficiency, and market trends – guiding strategic decisions, spotting inefficiencies, and identifying growth opportunities.

What is metadata?

Metadata is data that describes other data; it is the underlying definition or description of data, providing context, meaning, and usability. Examples of metadata include the properties of a media file: its size, type, resolution, author, and creation date. Software applications, documents, spreadsheets, and web pages are all examples that typically have associated metadata. Master data, reference data, and log data all have related metadata.

Metadata is crucial for data management activities such as integration, stewardship, and governance.

What is big data?

Big data has many different definitions, but the most common is from Gartner’s Doug Laney. He characterized “big data” by 3Vs: volume, variety, and velocity. By its very nature, big data cannot be effectively maintained with traditional technology. Quite simply, it combines the previous four types of data: log data, transactional data, reference data, and master data.

What is unstructured data?

Unstructured Data is data that does not have a predefined structure. This type of data refers mainly to text data. For example, a PDF document enters in this category. Domains such as Text Mining can extract relevant and structured data from unstructured documents.

Master data types and how they influence business decisions

Some data categories hold immense relevance and critical influence, directly shaping business operations and decisions. Think of them as the pillars supporting the business structure and guiding its strategies. Among these, three specific MDM types – customer data, product data, and financial data – are fundamental. They form the backbone of any organization, offering crucial insights into customer behavior, product performance, and financial health. Understanding these types of master data and their applications within a business is essential for unlocking opportunities and fueling business growth.

Customer data

This master data category comprises customer information such as contact details, purchase history, and preferences. It plays a vital role in sales and marketing, customer service, and analytics. Many businesses use customer master data management software to control this vital information.

Product data

This category includes comprehensive details about products and services, including descriptions, specifications, pricing, and availability. It’s vital for inventory management, sales, marketing, and supply chain operations – so it’s a good idea to use product master data management software.

Financial data

This type involves a business’s financial transactions, accounts, and reports. Finance master data management software helps companies stay in control of their financial health and meet regulatory requirements.

Employee data

This includes details about employees within an organization, such as personal information, job history, skills, and qualifications. Employee data is crucial for HR management, payroll processing, talent development, and compliance. Numerous companies use employee master data management software to maintain accurate and up-to-date personnel records.

Location data

This category involves details about different geographical locations relevant to an organization, including addresses, coordinates, and site-specific information. Essential for logistics, facility management, and location-based analytics, location master data management software is a valuable tool.

Asset data

This data type includes details about assets owned or operated by a company, including descriptions, specifications, maintenance schedules, and depreciation values. Such data is critical for asset tracking, maintenance planning, and financial accounting, using asset master data management software.

Materials data

This master data category comprises information related to materials or resources used in a company’s operations, including material descriptions, properties, quantities, suppliers, and costs. Materials master data management software can effectively manage this type of data.

Supplier or vendor data

This involves all the information associated with the suppliers or vendors engaged by a business, including contact details, contractual terms, performance history, and certifications. Supplier master data management software can handle this type of data with ease.

Master data types like these are pivotal in shaping business decisions by offering comprehensive and accurate insights into essential aspects of the business.

So, what’s the problem with master data?

As mentioned earlier, Master data is often authored (created) and used in operational systems but is not always accurate and complete enough to fit all purposes.

For example, a phone device ordering process (or application) would probably go beyond gathering only order-related data. Billing and shipping addresses of the party placing the order would also be provided. But the email address, since it is not relevant in this process would probably not be created. A web registration process would focus on the quality of the email address, but would not guarantee the quality of the phone number, etc. Data entered in these applications is indeed tailored for each application-specific scenario and usage. But at the enterprise level, such customer master data should include accurate billing/shipping addresses as well as a valid email address and phone number.

In the organization of data, transactional and reporting data rely on master (and reference) data. As a consequence, “bad master data” reflects directly into untrustworthy reports and operational inefficiency.

What is golden data?

Now, imagine a database hosting customers (or products, employees, sites) records with:

• • All the relevant information (aggregated from the various operational sources),

• • Only valid information (No incorrect addresses or bouncing emails),

• • No duplicates.

This database would be golden data. Golden data is a cleansed, de-duplicated, consolidated, validated version of the original master data. Some people call it the “Single Version of The Truth” or “360° Customer View” (needless to say that Capital Letters are a must here).

As you may imagine, this golden data has tremendous value for applications (BI, operational, or others). It also reveals other challenges, that will be discussed in future posts.

Bring it all together: Semarchy Data Platform

Semarchy’s Data Platform brings together information that lives across applications such that it can be governed, mastered, and managed in a centrally understood, non-disruptive way.

Book a demo today.