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Data Steward
A data steward is an oversight or data governance role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization's data assets, including the metadata for those data assets. A data steward may share some responsibilities with a data custodian, such as the awareness, accessibility, release, appropriate use, security and management of data. A data steward would also participate in the development and implementation of data assets. A data steward may seek to improve the quality and fitness for purpose of other data assets their organization depends upon but is not responsible for. Data stewards have a specialist role that utilizes an organization's data governance processes, policies, guidelines and responsibilities for administering an organizations' entire data in compliance with policy and/or regulatory obligations. The overall objective of a data steward is the data quality of the data assets, datasets, data records and dat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ETH Zurich
ETH Zurich (; ) is a public university in Zurich, Switzerland. Founded in 1854 with the stated mission to educate engineers and scientists, the university focuses primarily on science, technology, engineering, and mathematics. ETH Zurich ranks among Europe's best universities. Like its sister institution École Polytechnique Fédérale de Lausanne, EPFL, ETH Zurich is part of the ETH Domain, Swiss Federal Institutes of Technology Domain, a consortium of universities and research institutes under the Swiss Federal Department of Economic Affairs, Education and Research. , ETH Zurich enrolled 25,380 students from over 120 countries, of which 4,425 were pursuing doctoral degrees. Students, faculty, and researchers affiliated with ETH Zurich include 22 Nobel Prize, Nobel laureates, two Fields Medalists, three Pritzker Architecture Prize, Pritzker Prize winners, and one Turing Award, Turing Award recipient, including Albert Einstein and John von Neumann. It is a founding member o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information Technology Governance
Information technology (IT) governance is a subset discipline of corporate governance, focused on information technology (IT) and its performance and risk management. The interest in IT governance is due to the ongoing need within organizations to focus value creation efforts on an organization's strategic objectives and to better manage the performance of those responsible for creating this value in the best interest of all stakeholders. It has evolved from The Principles of Scientific Management, Total Quality Management and ISO 9001 Quality Management System. Historically, board-level executives deferred key IT decisions to the company's IT management and business leaders. Short-term goals of those responsible for managing IT can conflict with the best interests of other stakeholders unless proper oversight is established. IT governance systematically involves everyone: board members, executive management, staff, customers, communities, investors and regulators. An IT Gov ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Management
Data management comprises all disciplines related to handling data as a valuable resource, it is the practice of managing an organization's data so it can be analyzed for decision making. Concept The concept of data management emerged alongside the evolution of computing technology. In the 1950s, as computers became more prevalent, organizations began to grapple with the challenge of organizing and storing data efficiently. Early methods relied on punch cards and manual sorting, which were labor-intensive and prone to errors. The introduction of database management systems in the 1970s marked a significant milestone, enabling structured storage and retrieval of data. By the 1980s, relational database models revolutionized data management, emphasizing the importance of data as an asset and fostering a data-centric mindset in business. This era also saw the rise of data governance practices, which prioritized the organization and regulation of data to ensure quality and complian ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ralph Kimball
Ralph Kimball (born July 18, 1944) is an author on the subject of data warehousing and business intelligence. He is one of the original architects of data warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast. His bottom-up methodology, also known as dimensional modeling or the Kimball methodology, is one of the two main data warehousing methodologies alongside Bill Inmon. He is the principal author of the best-selling books ''The Data Warehouse Toolkit'' (1996), ''The Data Warehouse Lifecycle Toolkit'' (1998), ''The Data Warehouse ETL Toolkit'' (2004) and ''The Kimball Group Reader'' (2015), published by Wiley and Sons. Career After receiving a Ph.D. in 1973 from Stanford University in electrical engineering (specializing in man-machine systems), Ralph joined the Xerox Palo Alto Research Center (PARC). At PARC Ralph was a principal designer of the Xerox Star Workstation, the first commercial product to use mice ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ISO/IEC 11179
The ISO/IEC 11179 metadata registry (MDR) standard is an international International Organization for Standardization, ISO/International Electrotechnical Commission, IEC standard for representing metadata for an organization in a metadata registry. It documents the standardization and registration of metadata to make data understandable and shareable. Structure of an ISO/IEC 11179 metadata registry The ISO/IEC 11179 model is a result of two principles of semantic theory, combined with basic principles of data modelling. The first principle from semantic theory is the thesaurus type relation between wider and more narrow (or specific) concepts, e.g. the wide concept "income" has a relation to the more narrow concept "net income". The second principle from semantic theory is the relation between a concept and its representation, e.g., "buy" and "purchase" are the same concept although different terms are used. A basic principle of data modelling is the combination of an object c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Representation Term
A representation term is a word, or a combination of words, that semantically represent the data type (value domain) of a data element. A representation term is commonly referred to as a ''class word'' by those familiar with data dictionaries. ISO/IEC 11179-5:2005 defines ''representation term'' as a ''designation of an instance of a representation class'' As used in ISO/IEC 11179, the representation term is that part of a data element name that provides a semantic pointer to the underlying data type. A '' Representation class'' is a class of representations. This ''representation class'' provides a way to classify or group data elements. A ''Representation Term'' may be thought of as an attribute of a data element in a metadata registry that classifies the data element according to the type of data stored in the data element. Representation terms are typically "approved" by the organization or standards body using them. For example, the UN publishes its approved list as part ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Element Definition
In metadata, a data element definition is a human readable phrase or sentence associated with a data element within a data dictionary that describes the meaning or semantics of a data element. Data element definitions are critical for external users of any data system. Good definitions can dramatically ease the process of mapping one set of data into another set of data. This is a core feature of distributed computing and intelligent agent development. There are several guidelines that should be followed when creating high-quality data element definitions. Properties of clear definitions A good definition is: # Precise - The definition should use words that have a precise meaning. Try to avoid words that have multiple meanings or multiple word senses. The definition should use the shortest description. The definition should not use the term you are trying to define in the definition itself. This is known as a circular definition. # Distinct - The definition should differentia ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Element
In metadata, the term data element is an atomic unit of data that has precise meaning or precise semantics. A data element has: # An identification such as a data element name # A clear data element definition # One or more representation terms # Optional enumerated values Code (metadata) # A list of synonyms to data elements in other metadata registries Synonym ring Data elements usage can be discovered by inspection of software applications or application data files through a process of manual or automated Application Discovery and Understanding. Once data elements are discovered they can be registered in a metadata registry. In telecommunications, the term data element has the following components: #A named unit of data that, in some contexts, is considered indivisible and in other contexts may consist of data items. #A named identifier of each of the entities and their attributes that are represented in a database. #A basic unit of information built on standard stru ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Curation
Data ( , ) are a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information can be extracted. Data are collected using techniques suc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Metadata Registry
A metadata registry is a central location in an organization where metadata definitions are stored and maintained in a controlled method. A metadata repository is the database where metadata is stored. The registry also adds relationships with related metadata types. A metadata engine collects, stores and analyzes information about data and metadata (data about data) in use within a domain. Use of metadata registries Metadata registries are used whenever data must be used consistently within an organization or group of organizations. Examples of these situations include: * Organizations that transmit data using structures such as XML, Web Services or EDI * Organizations that need consistent definitions of data across time, between databases, between organizations or between processes, for example when an organization builds a data warehouse * Organizations that are attempting to break down "silos" of information captured within applications or proprietary file formats Central ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
