Data Vault Modeling
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Data Vault Modeling
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 (database), 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. It was developed by Daniel Linstedt, Daniel (Dan) Linstedt in 2000. 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 ...
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Database
In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance. A database management system (DBMS) is the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS software additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an appli ...
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Extract, Transform, Load
In computing, extract, transform, load (ETL) is a three-phase process where data is extracted, transformed (cleaned, sanitized, scrubbed) and loaded into an output data container. The data can be collated from one or more sources and it can also be outputted to one or more destinations. ETL processing is typically executed using software applications but it can also be done manually by system operators. ETL software typically automates the entire process and can be run manually or on reoccurring schedules either as single jobs or aggregated into a batch of jobs. A properly designed ETL system extracts data from source systems and enforces data type and data validity standards and ensures it conforms structurally to the requirements of the output. Some ETL systems can also deliver data in a presentation-ready format so that application developers can build applications and end users can make decisions. The ETL process became a popular concept in the 1970s and is often used in d ...
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Vehicle Identification Number
A vehicle identification number (VIN) (also called a chassis number or frame number) is a unique code, including a serial number, used by the automotive industry to identify individual motor vehicles, towed vehicles, motorcycles, scooters and mopeds, as defined by the International Organization for Standardization in ISO 3779 (content and structure) and ISO 4030 (location and attachment). There are vehicle history services in several countries that help potential car owners use VINs to find vehicles that are defective or have been written off. History of the bodywork number VINs were first used in 1954 in the United States. From 1954 to 1981, there was no accepted standard for these numbers, so different manufacturers used different formats. In 1981, the National Highway Traffic Safety Administration of the United States standardized the format. It required all on-road vehicles sold to contain a 17-character VIN, which does not include the letters O (o), I (i), and Q (q ...
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Natural Key
A natural key (also known as business key or domain key) is a type of unique key in a database formed of attributes that exist and are used in the external world outside the database (i.e. in the business domain or domain of discourse). In the relational model of data, a natural key is a superkey and is therefore a functional determinant for all attributes in a relation. A natural key serves two complementary purposes: it provides a means of identification for data and it imposes a rule, specifically a ''uniqueness constraint'', to ensure that data remains unique within an information system. The uniqueness constraint assures uniqueness of data within a certain technical context (e.g. a set of values in a table, file or relation variable) by rejecting input of any data that would otherwise violate the constraint. This means that the user can rely on a guaranteed correspondence between facts identified by key values recorded in a system and the external domain of discourse (a single ...
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Surrogate Key
A surrogate key (or synthetic key, pseudokey, entity identifier, factless key, or technical key) in a database is a unique identifier for either an ''entity'' in the modeled world or an ''object'' in the database. The surrogate key is ''not'' derived from application data, unlike a ''natural'' (or ''business'') key. Definition There are at least two definitions of a surrogate: ; Surrogate (1) – Hall, Owlett and Todd (1976): A surrogate represents an ''entity'' in the outside world. The surrogate is internally generated by the system but is nevertheless visible to the user or application. ; Surrogate (2) – Wieringa and De Jonge (1991): A surrogate represents an ''object'' in the database itself. The surrogate is internally generated by the system and is invisible to the user or application. The ''Surrogate (1)'' definition relates to a data model rather than a storage model and is used throughout this article. See Date (1998). An important distinction between a s ...
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Data Vault Example
In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which 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 is commonly used in scientific research, economics, and in virtually every other form of human organizational activity. Examples of data sets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures which can be used in such a manner in order to capture the useful information out of it. Dat ...
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Ontology (information Science)
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject. Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. For instance, the definition and ontology of economics is a primary concern in Marxist econo ...
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