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Data Vault Modelling
Datavault or data vault modeling is a database modeling method that is designed to provide long-term historical storage of data coming in from multiple operational systems. It is also a method of looking at historical data that deals with issues such as auditing, tracing of data, loading speed and resilience to change as well as emphasizing the need to trace where all the data in the database came from. This means that every row in a data vault must be accompanied by record source and load date attributes, enabling an auditor to trace values back to the source. The concept was published in 2000 by Dan Linstedt. Data vault modeling makes no distinction between good and bad data ("bad" meaning not conforming to business rules). This is summarized in the statement that a data vault stores " a single version of the facts" (also expressed by Dan Linstedt as "all the data, all of the time") as opposed to the practice in other data warehouse methods of storing "a single version of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Vault Example
Data ( , ) are a collection of discrete or continuous value (semiotics), values that convey information, describing the quantity, qualitative property, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpretation (logic), interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as table (information), tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be Data (computer science), used as variable (research), 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 repr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Relational Model
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, where all data are represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a relational database. The purpose of the relational model is to provide a declarative method for specifying data and queries: users directly state what information the database contains and what information they want from it, and let the database management system software take care of describing data structures for storing the data and retrieval procedures for answering queries. Most relational databases use the SQL data definition and query language; these systems implement what can be regarded as an engineering approximation to the relational model. A '' table'' in a SQL database schema corresponds to a predicate variable; the contents of a tab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Software Engineering Institute
Software Engineering Institute (SEI) is a Federally funded research and development centers, federally funded research and development center in Pittsburgh, Pennsylvania, United States. Founded in 1984, the institute is now sponsored by the United States Department of Defense and the Under Secretary of Defense for Research and Engineering, Office of the Under Secretary of Defense for Research and Engineering, and administrated by Carnegie Mellon University. The activities of the institute cover cybersecurity, software assurance, software engineering and acquisition, and component capabilities critical to the United States Department of Defense. Authority The Carnegie Mellon Software Engineering Institute is a federally funded research and development center headquartered on the campus of Carnegie Mellon University in Pittsburgh, Pennsylvania, United States. The SEI also has offices in Washington, DC; Arlington County, Virginia; and Los Angeles, California. The SEI operates wi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Open Standard
An open standard is a standard that is openly accessible and usable by anyone. It is also a common prerequisite that open standards use an open license that provides for extensibility. Typically, anybody can participate in their development due to their inherently open nature. There is no single definition, and interpretations vary with usage. Examples of open standards include the GSM, 4G, and 5G standards that allow most modern mobile phones to work world-wide. Definitions The terms ''open'' and ''standard'' have a wide range of meanings associated with their usage. There are a number of definitions of open standards which emphasize different aspects of openness, including the openness of the resulting specification, the openness of the drafting process, and the ownership of rights in the standard. The term "standard" is sometimes restricted to technologies approved by formalized committees that are open to participation by all interested parties and operate on a consensus basis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Normal Forms
Database normalization is the process of structuring a relational database in accordance with a series of so-called '' normal forms'' in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes) and tables (relations) of a database to ensure that their dependencies are properly enforced by database integrity constraints. It is accomplished by applying some formal rules either by a process of ''synthesis'' (creating a new database design) or ''decomposition'' (improving an existing database design). Objectives A basic objective of the first normal form defined by Codd in 1970 was to permit data to be queried and manipulated using a "universal data sub-language" grounded in first-order logic. An example of such a language is SQL, though it is one that Codd regarded as seriously flawed. The objectives of normaliza ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bill Inmon
William H. Inmon (born 1945) is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, held the first conference (with Arnie Barnett), wrote the first column in a magazine and was the first to offer classes in data warehousing. Inmon created the accepted definition of what a data warehouse is - a subject-oriented, non-volatile, integrated, time-variant collection of data in support of management's decisions. Compared with the approach of the other pioneering architect of data warehousing, Ralph Kimball, Inmon's approach is often characterized as a top-down approach. Biography William H. Inmon was born July 20, 1945, in San Diego, California. He received his Bachelor of Science degree in mathematics from Yale University in 1967, and his Master of Science degree in computer science from New Mexico State University. He worked for American Management Systems and Coopers & Lybrand before 1991, when he founded the compa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Enterprise Bus Matrix
The enterprise bus matrix is a data warehouse planning tool and model created by Ralph Kimball, and is part of the data warehouse bus architecture. The matrix is the logical definition of one of the core concepts of Kimball's approach to dimensional modeling conformed dimension. The bus matrix defines part of the data warehouse bus architecture and is an output of the business requirements phase in the Kimball lifecycle. It is applied in the following phases of dimensional modeling and development of the data warehouse. The matrix can be categorized as a hybrid model, being part technical design tool, part project management tool and part communication toolKimball, Ralph & Ross, Margy; The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd Edition John Wiley & Sons, 2002 Background The need for an enterprise bus matrix stems from the way one goes about creating the overall data warehouse environment. Historically there have been two approaches: a structured, ... [...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] |
Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for Business intelligence, reporting and data analysis and is a core component of business intelligence. Data warehouses are central Repository (version control), repositories of data integrated from disparate sources. They store current and historical data organized in a way that is optimized for data analysis, generation of reports, and developing insights across the integrated data. They are intended to be used by analysts and managers to help make organizational decisions. The data stored in the warehouse is uploaded from operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the data warehouse for reporting. The two main workflows for building a data warehouse system are extract, transform, load (ETL) and extract, load, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
