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Denormalization
Denormalization is a strategy used on a previously- normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data.S. K. Shin and G. L. SandersDenormalization strategies for data retrieval from data warehouses Decision Support Systems, 42(1):267-282, October 2006. It is often motivated by performance or scalability in relational database software needing to carry out very large numbers of read operations. Denormalization differs from the unnormalized form in that denormalization benefits can only be fully realized on a data model that is otherwise normalized. Implementation A normalized design will often "store" different but related pieces of information in separate logical tables (called relations). If these relations are stored physically as separate disk files, completing a database que ...
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Database
In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS 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 application associated with the database. Before digital storage and retrieval of data have become widespread, index cards were used for data storage in a wide range of applications and environments: in the home to record and store recipes, shopping lists, contact information and other organizational data; in business to record presentation notes, project research and notes, and contact information; in schools as flash c ...
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Star Schema
In computing, the star schema or star model is the simplest style of data mart Logical schema, schema and is the approach most widely used to develop data warehouses and dimensional data marts. The star schema consists of one or more fact tables referencing any number of Dimension (data warehouse), dimension tables. The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. The star schema gets its name from the Physical data model, physical model'sC J Date, "An Introduction to Database Systems (Eighth Edition)", p. 708 resemblance to a Star polygon, star shape with a fact table at its center and the dimension tables surrounding it representing the star's points. Model The star schema separates business process data into facts, which hold the measurable, quantitative data about a business, and dimensions which are descriptive attributes related to fact data. Examples of fact data include sales price, sale quantity, ...
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DBMS
In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS 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 application associated with the database. Before digital storage and retrieval of data have become widespread, index cards were used for data storage in a wide range of applications and environments: in the home to record and store recipes, shopping lists, contact information and other organizational data; in business to record presentation notes, project research and notes, and contact information; in schools as flash card ...
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Unnormalized Form
In database normalization, unnormalized form (UNF or 0NF), also known as an unnormalized relation or non-first normal form (N1NF or NF2), is a database data model (organization of data in a database) which does not meet any of the conditions of database normalization defined by the relational model. Database systems which support unnormalized data are sometimes called non-relational or NoSQL databases. In the relational model, unnormalized relations can be considered the starting point for a process of normalization. "Unnormalized form" should not be confused with denormalization, where normalization is deliberately compromised for selected tables in a relational database. History In 1970, E. F. Codd proposed the relational data model, now widely accepted as the standard data model. At that time, office automation was the major use of data storage systems, which resulted in the proposal of many UNF/NF2 data models like the Schek model, Jaeschke models ( non-recursive and recur ...
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Database Management System
In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS 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 application associated with the database. Before digital storage and retrieval of data have become widespread, index cards were used for data storage in a wide range of applications and environments: in the home to record and store recipes, shopping lists, contact information and other organizational data; in business to record presentation notes, project research and notes, and contact information; in schools as flash ca ...
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Database Normalization
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 normalization ...
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Constraint Satisfaction
In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. A solution is therefore an assignment of values to the variables that satisfies all constraints—that is, a point in the feasible region. The techniques used in constraint satisfaction depend on the kind of constraints being considered. Often used are constraints on a finite domain, to the point that constraint satisfaction problems are typically identified with problems based on constraints on a finite domain. Such problems are usually solved via search, in particular a form of backtracking or local search. Constraint propagation is another family of methods used on such problems; most of them are incomplete in general, that is, they may solve the problem or prove it unsatisfiable, but not always. Constraint propagation methods are also used in conjunction with search to make ...
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OLAP Cube
An OLAP cube is a multi-dimensional array of data. Online analytical processing (OLAP) is a computer-based technique of analyzing data to look for insights. The term ''cube'' here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three. Terminology A cube can be considered a multi-dimensional generalization of a two- or three-dimensional spreadsheet. For example, a company might wish to summarize financial data by product, by time-period, and by city to compare actual and budget expenses. Product, time, city and scenario (actual and budget) are the data's dimensions. ''Cube'' is a shorthand for ''multidimensional dataset'', given that data can have an arbitrary number of ''Dimension (data warehouse), dimensions''. The term hypercube is sometimes used, especially for data with more than three dimensions. A cube is not a "cube" in the strict mathematical sense, as the sides are not all necessarily equal. ...
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Snowflake Schema
In computing, a snowflake schema or snowflake model is a Logical schema, logical arrangement of tables in a multidimensional database such that the Entity-relationship model, entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which are connected to multiple Dimension (data warehouse), dimensions. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle behind snowflaking is normalization of the dimension tables by removing low cardinality attributes and forming separate tables. The snowflake schema is similar to the star schema. However, in the snowflake schema, dimensions are Normalization (database), normalized into multiple related tables, whereas the star schema's dimensions are denormalized with each dimension represented by ...
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One-to-many (data Model)
In systems analysis, a one-to-many relationship is a type of cardinality that refers to the relationship between two entities (see also entity–relationship model). For example, take a car and an owner of the car. The car can only be owned by one owner at a time or not owned at all, and an owner could own zero, one, or multiple cars. One owner could have many cars, one-to-many. In a relational database, a one-to-many relationship exists when one record is related to many records of another table. A one-to-many relationship is not a property of the data, but rather of the relationship itself. One-to-many often refer to a primary key to foreign key relationship between two tables, where the record in the first table can relate to multiple records in the second table. A foreign key is one side of the relationship that shows a row or multiple rows, with one of those rows being the primary key already listed on the first table. This is also called a foreign key constraint, which is i ...
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Multivalued Dependency
In database theory, a multivalued dependency is a full constraint between two sets of attributes in a relation. In contrast to the functional dependency, the multivalued dependency requires that certain tuples be present in a relation. Therefore, a multivalued dependency is a special case of tuple-generating dependency. The multivalued dependency plays a role in the 4NF database normalization. A multivalued dependency is a special case of a join dependency, with only two sets of values involved, i.e. it is a binary join dependency. A multivalued dependency exists when there are at least three attributes (like X,Y and Z) in a relation and for a value of X there is a well defined set of values of Y and a well defined set of values of Z. However, the set of values of Y is independent of set Z and vice versa. Formal definition The formal definition is as follows: Let R be a relation schema and let \alpha \subseteq R and \beta \subseteq R be sets of attributes. The multivalue ...
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Join Dependency
In database theory, a join dependency is a constraint on the set of legal relations over a database scheme. A table T is subject to a join dependency if T can always be recreated by joining multiple tables each having a subset of the attributes of T. If one of the tables in the join has all the attributes of the table T, the join dependency is called trivial. The join dependency plays an important role in the fifth normal form (5NF), also known as ''project-join normal form'', because it can be proven that if a scheme R is decomposed in tables R_1 to R_n, the decomposition will be a lossless-join decomposition if the legal relations on R are restricted to a join dependency on R called *(R_1,R_2,\ldots,R_n). Another way to describe a join dependency is to say that the relationships in the join dependency are independent of each other. Unlike in the case of functional dependencies, there is no sound and complete axiomatization for join dependencies, though axiomatization exist f ...
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