The Beauty of Master Data Management

In a world with ever more data being generated and ever more functionality to be attend from that data, the importance of maintaining that data has never been so crucial.Maintaining uniformity across all machines in different countries, timezones and departments can be a nightmare for big businesses. In order to gain the maximum benefit from this data and to be able to use it in the most efficient way a business needs to implement a Master Data Management Program.

Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets. 

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, 2013)

Knowing that we need to keep track of our data is a no brainer. But how do we define this data?

There are essentially five types of data in corporations:

Unstructured — This is data found in e-mail, white papers like this, magazine articles, corporate intranet portals, product specifications, marketing collateral, and PDF files.

Transactional — This is data related to sales, deliveries, invoices, trouble tickets, claims, and other monetary and non-monetary interactions.

Metadata — This is data about other data and may reside in a formal repository or in various other forms such as XML documents, report definitions, column descriptions in a database, log files, connections, and configuration files.

Hierarchical — Hierarchical data stores the relationships between other data. It may be stored as part of an accounting system or separately as descriptions of real-world relationships, such as company organizational structures or product lines. Hierarchical data is sometimes considered a super MDM domain, because it is critical to understanding and sometimes discovering the relationships between master data.

Master — 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. For example, within people, there are customer, employee, and salesperson. Within things, there are product, part, store, and asset. Within concepts, there are things like contract, warrantee, and licenses. Finally, within places, there are office locations and geographic divisions. Some of these domain areas may be further divided. Customer may be further segmented, based on incentives and history. A company may have normal customers, as well as premiere and executive customers. Product may be further segmented by sector and industry. The requirements, life cycle, and CRUD cycle for a product in the Consumer Packaged Goods (CPG) sector is likely very different from those of the clothing industry. The granularity of domains is essentially determined by the magnitude of differences between the attributes of the entities within them.(Walter and Haselden, 2006)

This Master data is some of the most important data the a company can gather. But as more and more data is generated in the everyday business processes of a company, we need to have systems in place to process and store this data in an effective way the allows those in the company who can benefit from it to have access and to protect the often sensitive information that is collected in the day to interactions between companies and consumers.

In order to enable MDM we need to follow process of

ETL: Extract, Transform, Load. A process in database usage and especially in data warehousing that performs: Data extraction – extracts data from homogeneous or heterogeneous data sources. (Wikepedia 2016)

EAI: Enterprise application integration: the use of software and computer systems’ architectural principles to integrate a set of enterprise computer applications. (Wikipedia 2016)

EII: Enterprise information integration, is the ability to support a unified view of data and information for an entire organisation.(Wikipedia 2016)

For a layman breakdown of these terms refer to this handy guide:

All of these processes come together to store information in a uniform manner that accounts for repetition and keeps data uniform, separate and accurate when applied in tandem with a strong data governance program.

Source: Gartner (2013) Accessed 26/05/2014.

Walter and Haselden (2006) Accessed 12/09/16

Wikipedia (2016),_transform,_load accessed 12/09/16

Wikipedia (2016) accessed

Wikipedia (2016) accessed 12/09/16

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