Master data

Last updated

Master data represents "data about the business entities that provide context for business transactions". [1] The most commonly found categories of master data are parties (individuals and organisations, and their roles, such as customers, suppliers, employees), products, financial structures (such as ledgers and cost centres) and locational concepts. [1] [2]

Contents

Master data should be distinguished from reference data. While both provide context for business transactions, reference data is concerned with classification and categorisation, while master data is concerned with business entities.

Master data is, by its nature, almost always non-transactional in nature. There exist edge cases where an organization may need to treat certain transactional processes and operations as "master data". This arises, for example, where information about master data entities, such as customers or products, is only contained within transactional data such as orders and receipts and is not housed separately. [3]

Alternative definition

An alternative definition of the term master data is that it represents the business objects that contain the most valuable, agreed upon information shared across an organization. [4] In this sense, it gives context to business activities and transactions, answering questions like who, what, when and how as well as expanding the ability to make sense of these activities through categorizations, groupings and hierarchies. It can cover relatively static reference data, transactional, unstructured, analytical, hierarchical and metadata. [5] What constitutes master data under this definition is therefore not about an essential quality of the data (e.g. it is a business entity that provides context for business transactions), but rather about the context in which the organisation has decided to treat the data.

Externally-defined master data

For most organisations, most or all master data is defined and managed within that organisation.

Some master data, however, may be externally defined and managed. This represents the single source of basic business data used across a marketplace, regardless of organisation or location. Thus, 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." [6] An example of market master data is the Universal Product Code (UPC) found on consumer products.

Master data management

Curating and managing master data is key to ensuring its quality and thus fitness for purpose. All aspects of an organisation, operational and analytical, are greatly dependent on the quality of an organization's master data. Master Data is therefore the focus of the information technology (IT) discipline of master data management (MDM). Without this discipline in place, organisations commonly encounter difficulties with having multiple versions of "the truth" about a business entity, both within individual applications, and distributed across applications.

Related Research Articles

<span class="mw-page-title-main">Data warehouse</span> Centralized storage of knowledge

In computing, a data warehouse, also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.

Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.

A business process, business method or business function is a collection of related, structured activities or tasks by people or equipment in which a specific sequence produces a service or product for a particular customer or customers. Business processes occur at all organizational levels and may or may not be visible to the customers. A business process may often be visualized (modeled) as a flowchart of a sequence of activities with interleaving decision points or as a process matrix of a sequence of activities with relevance rules based on data in the process. The benefits of using business processes include improved customer satisfaction and improved agility for reacting to rapid market change. Process-oriented organizations break down the barriers of structural departments and try to avoid functional silos.

<span class="mw-page-title-main">Data management</span> Disciplines related to managing data as a resource

Data management comprises all disciplines related to handling data as a valuable resource.

Identity management (IdM), also known as identity and access management, is a framework of policies and technologies to ensure that the right users have the appropriate access to technology resources. IdM systems fall under the overarching umbrellas of IT security and data management. Identity and access management systems not only identify, authenticate, and control access for individuals who will be utilizing IT resources but also the hardware and applications employees need to access.

Essbase is a multidimensional database management system (MDBMS) that provides a platform upon which to build analytic applications. Essbase began as a product from Arbor Software, which merged with Hyperion Software in 1998. Oracle Corporation acquired Hyperion Solutions Corporation in 2007. Until late 2005 IBM also marketed an OEM version of Essbase as DB2 OLAP Server.

Software as a service is a software licensing and delivery model in which software is licensed on a subscription basis and is centrally hosted. SaaS is also known as "on-demand software" and Web-based/Web-hosted software.

Enterprise software, also known as enterprise application software (EAS), is computer software used to satisfy the needs of an organization rather than individual users. Such organizations include businesses, schools, interest-based user groups, clubs, charities, and governments. Enterprise software is an integral part of a (computer-based) information system; a collection of such software is called an enterprise system. These systems handle a number of operations in an organization to enhance the business and management reporting tasks. The systems must process the information at a relatively high speed and can be deployed across a variety of networks.

In online transaction processing (OLTP), information systems typically facilitate and manage transaction-oriented applications. This is contrasted with online analytical processing.

Data architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture.

In information science and information technology, single source of truth (SSOT) architecture, or single point of truth (SPOT) architecture, for information systems is the practice of structuring information models and associated data schemas such that every data element is mastered in only one place, providing data normalization to a canonical form. Any possible linkages to this data element are by reference only. Because all other locations of the data just refer back to the primary "source of truth" location, updates to the data element in the primary location propagate to the entire system, providing multiple advantages simultaneously: greater efficiency/productivity, easy prevention of mistaken inconsistencies, and greatly simplified version control. Without SSOT architecture, rampant forking impairs clarity and productivity, imposing laborious maintenance needs.

An information server is an integrated software platform consisting of a set of core functional modules that enables organizations to integrate data from disparate sources and deliver trusted and complete information, at the time it is required and in the format it is needed. Similar to how an application server is a software engine that delivers applications to client computers, an information server delivers consistent information to consuming applications, business processes and portals.

Microsoft SQL Server Master Data Services (MDS) is a Master Data Management (MDM) product from Microsoft that ships as a part of the Microsoft SQL Server relational database management system. Master data management (MDM) allows an organization to discover and define non-transactional lists of data, and compile maintainable, reliable master lists. Master Data Services first shipped with Microsoft SQL Server 2008 R2. Microsoft SQL Server 2016 introduced enhancements to Master Data Services, such as improved performance and security, and the ability to clear transaction logs, create custom indexes, share entity data between different models, and support for many-to-many relationships.

Microsoft SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network. Microsoft markets at least a dozen different editions of Microsoft SQL Server, aimed at different audiences and for workloads ranging from small single-machine applications to large Internet-facing applications with many concurrent users.

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

Reference data is data used to classify or categorize other data. Typically, they are static or slowly changing over time.

Business transaction management (BTM), also known as business transaction monitoring, application transaction profiling or user defined transaction profiling, is the practice of managing information technology (IT) from a business transaction perspective. It provides a tool for tracking the flow of transactions across IT infrastructure, in addition to detection, alerting, and correction of unexpected changes in business or technical conditions. BTM provides visibility into the flow of transactions across infrastructure tiers, including a dynamic mapping of the application topology.

ISO 8000 is the global standard for Data Quality and Enterprise Master Data. It describes the features and defines the requirements for standard exchange of Master Data among business partners. It establishes the concept of Portability as a requirement for Enterprise Master Data, and the concept that true Enterprise Master Data is unique to each organization.

Versant Object Database (VOD) is an object database software product developed by Versant Corporation.

<span class="mw-page-title-main">SAP HANA</span> Database management system by SAP

SAP HANA is an in-memory, column-oriented, relational database management system developed and marketed by SAP SE. Its primary function as the software running a database server is to store and retrieve data as requested by the applications. In addition, it performs advanced analytics and includes extract, transform, load (ETL) capabilities as well as an application server.

References

  1. 1 2 DAMA-DMBOK: Data Management Body of Knowledge. Data Management Association. 2017. ISBN   978-1634622349.
  2. "Gartner Glossary: Master Data Management" . Retrieved 6 June 2020.
  3. van der Lans, R. (2012). Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses. Elsevier. pp. 119–121. ISBN   9780123978172.
  4. 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.
  5. 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.
  6. Taylor, S.; Laylin, R. (2010). "Master Data Management for Media". SlideShare. Microsoft Corporation. Retrieved 27 July 2018.

Further reading

See also