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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]
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[edit]
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[edit]
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[edit]
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.
The markdown cell in Jupyter Notebook can display six levels of heading. For making a heading, start the syntax with # followed by a space and then the text. This will make the heading of level 1 – The biggest. To decrease the size of the heading start incrementing the number of #. JUPYTER NOTEBOOK CHEAT SHEET Learn PYTHON from experts at Keyboard Shortcuts Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. It is used for data cleaning and transformation, numerical simulation, statistical. Sometimes markdown doesn't make line breaks when you want them. To force a linebreak, use the following code: Indenting Use the greater than sign followed by a space, for example: Text that will be indented when the Markdown is rendered. Any subsequent text. Markdown jupyter cheat sheet. Jupyter Notebook Markdown Cheatsheet April 9, 2020 SqlBak mike Jupyter Notebook is a great tool for data analysis. And one of its greatest features is that you.
References[edit]
- ^ abDAMA-DMBOK: Data Management Body of Knowledge. Data Management Association. 2017. ISBN978-1634622349.
- ^'Gartner Glossary: Master Data Management'. Retrieved 6 June 2020.
- ^van der Lans, R. (2012). Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses. Elsevier. pp. 119–121. ISBN9780123978172.
- ^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. ISBN9780132704274.
- ^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.
- ^Taylor, S.; Laylin, R. (2010). 'Master Data Management for Media'. SlideShare. Microsoft Corporation. Retrieved 27 July 2018.
Further reading[edit]
- Berson, Alex (2011). Master Data Management and Data Governance. McGraw-Hill Osborne Media. ISBN978-0071744584.
- Loshin, David (2006), 'Defining Master Data', BeyeNetwork. Retrieved 6 June 2020.
- Whei-Jen, Chen (2014). Master Data Management for SaaS Applications. IBM Redbooks. ISBN978-0738440040.
See also[edit]
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Enterprise-grade IT Technology,
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Datto delivers a single toolbox of easy to use products and services designed specifically for managed service providers and the businesses they serve. Datto's industry-leading MSP tools are designed to optimize your business and expand the services you deliver to clients. Our integrated, scalable, and innovative suite of hardware and software solutions work together to drive success for MSPs of any size.
See How Partnering with Datto Can Transform Your Business
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