“Master data are the critical nouns of a business and fall generally into four groupings: people, things, places, and concepts. Further categorizations within those groupings are called subject areas, domain areas, or entity types…Master data can be described by the way that it interacts with other data. For example, in transaction systems, master data is almost always involved with transactional data. A customer buys a product. A vendor sells a part, and a partner delivers a crate of materials to a location… Master data can be described by the way that it is Created, Read, Updated, Deleted, and searched. This life cycle is called the CRUD cycle…Why should I manage master data? Because it is used by multiple applications, an error in master data can cause errors in all the applications that use it. (“The What, Why, and How of Master Data Management” by Wolter and Haselden, Microsoft Corporation, November 2006)
- Single-copy of master data—where all changes and additions are made to the master and all applications accessing it use the current master data set
- Multiple copies of master data—master data is updated in a single master, but the data is sent out to the source systems where data sets are stored locally and changes to non-master data can be made)
- Continuous merge—where changes are made to the source data sets and are sent to the master to be merged and resent out to the source data sets again.
CIO.com, in “Demystifying Master Data Management”,
So the essence of an
- Information sharing—MDM is critical to information sharing, data integration, and reconciliation, as it establishes an authoritative source of data that can be shared between systems or organizational entities.
- Data governance—
MDMhelps establish the basis for sound data governance, since data owners, stewards, and users need to be able to distinguish good data from bad data, define data objects, establish data standards, metadata requirements and registries for discoverability, access rights, transfer protocols and methods, and maybe most importantly a governance process that defines who is allowed to change system data and how.
- Business Intelligence—
MDMenables business intelligence by providing for an integration of data for mining, reporting, and decision support.
Creating authoritative master data is an imperative for data and systems integrity, and good decision making based on sound enterprise data.