Master data refers to the core, non-transactional data that an organization uses repeatedly across its business operations. It represents key business entities and provides a single, consistent reference point for day-to-day processes and reporting. Unlike transactional data, which records individual events, master data are relatively stable and is shared across multiple systems and departments. Common examples of master data include customers, products, and employees.
Common categories for master data include:
These data sets serve as the foundation for business transactions. Other master data may also include warehouses, store branches, and more.
While master data defines who or what the business operates on, transactional data records what happens in daily operations. For example, a customer list is master data, and a sales order placed by that customer is transactional data. Transactions reference master data to ensure accuracy and consistency.
Maintaining high quality master data is critical because it ensures consistent information across systems and departments, reduces duplication and data entry errors, improves operational efficiency, and supports accurate reporting and decision-making. Poorly managed master data can lead to incorrect transactions, reporting errors, and operational delays.
Organizations often face challenges such as as duplicate or inconsistent records across departments, unclear ownership or approval processes, manual data maintenance and validation, as well as difficulty synchronizing data between systems. Addressing these issues early helps maintain data reliability as systems scale.
In modern information systems, master data is typically stored in structured databases and referenced by all related processes. A few tips in managing master data include:
