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Business metadata is important because it can greatly facilitate the usefulness of the data to business people. A simple example of business metadata is a glossary entry. Hover functionality in an application or web form can enable a glossary definition to be shown when cursor is on a field or term.
Master data is data about the business entities that provide context for business transactions, such as parties, products, financial structures and locations. Learn how master data is distinguished from reference data, how it is managed and governed, and how it can be externally defined and shared across a marketplace.
Learn about the definition, history, functions, and applications of business intelligence (BI), a set of strategies and technologies for data analysis and management. Compare BI with competitive intelligence and business analytics, and explore the challenges of unstructured data.
Metadata is data that provides information about other data, such as the author, title, or keywords of a book or a web page. Learn about the different types of metadata, how they are created and managed, and how they are used for various purposes, such as discovery, identification, and surveillance.
Data are a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, or other basic units of meaning. Data are used in scientific research, economics, and other fields, and can be processed, analyzed, and visualized using various methods and techniques.
Business analytics (BA) is the skills, technologies, and practices for exploring and investigating past business performance to gain insight and drive planning. BA uses data and statistical methods to answer questions like why, what if, and what will happen next, and is related to management science and business intelligence.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Learn about the phases, sources, and methods of data analysis, as well as the related fields of data science, data mining, and data visualization.
A data steward is a role that ensures the quality and fitness for purpose of an organization's data assets. Learn about the types, responsibilities, and benefits of data stewardship, and see examples from research and business contexts.