Industry experts have several ways to define master data. They say:
“Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts.” – Gartner, Inc.
Master data is having “consistent definitions of business entities (e.g., customer or product) and data about them across multiple IT systems and possibly beyond the enterprise to partnering businesses.” – Philip Russom, TDWI
“A clear description of master data includes customer data items, like IDs. This data type is considered master data, versus quantitative data related to a single transaction, customer ID or other data (such as addresses and phone numbers), which are continuously used by a business to analyze customer behavior, establish contacts, or drive high-level research.” – Technopedia
The common theme in master data
No matter where it comes from, the definition of master data has several common themes.
Master data is critical for operational and analytical business decision-making.
Master data is scattered throughout the enterprise.
Master data establishes a standard definition for business-critical data that is shared across the enterprise and collectively represents a “single source of truth.”
How does Semarchy define master data?
Master data is your business-critical data that is stored in disparate systems across your enterprise.
The Four Categories of Master Data
Parties: everyone who conducts business with the enterprise, including customers, prospects, suppliers, and partners.
Things: what the enterprise sells, such as products and services.
Places: actual places and how they are segmented, such as geographies, locations, subsidiaries, sites, and zones.
Financial and Organizational: reporting and accounting categories, including organization structures, sales territories, chart of accounts, cost centers, business units, profit centers, and price lists.
Other Types of Data
To really understand master data, it’s important to take a look at other data in the enterprise that isn’t master data – but can sometimes look like it.
Reference Data: often considered a subset of master data, reference data, or reference master data, is shared by and used across different internal and external systems and used to give meaning to master data.
Transactional Data: Transactional data describes business events and it responsible for generating the largest volume of data in the enterprise. It resides in the CRM, ERP, SCM, or other systems.
Log Data: Log data records events or takes snapshots of process states at moments in time. It is extremely important to system operational efficiencies and preventive maintenance applications. Most big data, such as sensor data, machine data, and change-in-state data, are examples of log data.
Metadata: Metadata is data that describes other data; it is the underlying definition or description of data. Master data, reference data, and log data all have related metadata.
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 is the combination of the previous four types of data: log data, transactional data, reference data, and master data.
Master Data Management is simply the complete management of master data. It includes the cleaning, governance, tracking and control of all master data.Master Data Management consists of a set of processes, disciplines and technologies.