Master data represents the business objects that contain the most valuable, agreed upon information shared across an organization. It can cover relatively static reference data, transactional, unstructured, analytical, hierarchical and metadata. It is the primary focus of the information technology (IT) discipline of master data management (MDM).
Master data is usually non-transactional in nature, but in some cases gray areas exist where transactional processes and operations may be considered master data by an organization. For example, master data may contain information about customers, products, employees, materials, suppliers, and vendors. Though rare, if that information is only contained within transactional data such as orders and receipts and is not housed separately, it may be considered master data.
Types of data
- Reference data represents the set of permissible values to be used by other (master or transaction) data fields. Reference data classifies and describes data and normally changes slowly, reflecting changes in the modes of operation of the business, rather than changing in the normal course of business.
- Enterprise master data represents the single source of basic business data used across the entire enterprise, regardless of location.
- Market master data represents the single source of basic business data used across a marketplace, regardless of location. This stands in contrast from enterprise master data in that it can be used by multiple enterprises within a value chain, facilitating "integration of multiple data sources and literally [putting] everyone in the market on the same page." An example of market master data is the UPC (Universal Product Code) found on consumer products.
Master data management
Curating and managing master data is key to ensuring master data quality. Analysis and reporting is greatly dependent on the quality of an organization's master data. Master data may either be stored in a central repository, sourced from one or more systems, or referenced centrally using an index. However, when it is used by several functional groups it may be distributed and redundantly stored in different applications across an organization and this copy data may be inconsistent (and if so, inaccurate). Thus, master data should have an agreed-upon view that is shared across the organization. Care should be taken to properly version master data, if the need arises to modify it, to avoid issues with distributed copies.
- Dreibelbis, A.; Hechler, E.; Milman, I.; et al. (2008). "Chapter 1: Introducing Master Data Management". Enterprise Master Data Management: An SOA Approach to Managing Core Information. Pearson Education. pp. 1–3. ISBN 9780132704274.CS1 maint: Multiple names: authors list (link)
- Wolter, R.; Haselden, K. (November 2006). "The What, Why, and How of Master Data Management". Microsoft Corporation. Archived from the original on 14 July 2017. Retrieved 13 December 2017.CS1 maint: Multiple names: authors list (link)
- van der Lans, R. (2012). Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses. Elsevier. pp. 119–121. ISBN 9780123978172.
- Taylor, S.; Laylin, R. (2010). "Master Data Management for Media". SlideShare. Microsoft Corporation. Retrieved 27 July 2018.CS1 maint: Multiple names: authors list (link)
- "The Elephant in the Room – Master Data and Application Data", Andrew White, Gartner, 14 January 2014
- Dreibelbis, A.; Hechler, E.; Milman, I.; et al. (2008). "Chapter 3: MDM Reference Architecture". Enterprise Master Data Management: An SOA Approach to Managing Core Information. Pearson Education. pp. PT207–09. ISBN 9780132704274.CS1 maint: Multiple names: authors list (link)