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The rationale for normalizing to 1NF: [2] Allows presenting, storing and interchanging relational data in the form of regular two-dimensional arrays. Supporting nested relations would require more complex data structures. Simplifies the data language, since any data item can be identified just by relation name, attribute name and key.
Set operations in SQL is a type of operations which allow the results of multiple queries to be combined into a single result set. [ 1 ] Set operators in SQL include UNION , INTERSECT , and EXCEPT , which mathematically correspond to the concepts of union , intersection and set difference .
Based on an array algebra [7] specifically developed for database purposes, rasdaman adds a new attribute type, array, to the relational model. As this array definition is parametrized it constitutes a second-order construct or template; this fact is reflected by the second-order functionals in the algebra and query language.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
The SQL SELECT statement returns a result set of rows, from one or more tables. [1] [2] A SELECT statement retrieves zero or more rows from one or more database tables or database views. In most applications, SELECT is the most commonly used data manipulation language (DML) command. As SQL is a declarative programming language, SELECT queries ...
The relational algebra uses set union, set difference, and Cartesian product from set theory, and adds additional constraints to these operators to create new ones.. For set union and set difference, the two relations involved must be union-compatible—that is, the two relations must have the same set of attributes.
With the functional model, data is arranged in a grid of cells, but cells are identified by business concept instead of just row or column. Rather than worksheets, the objects of the functional model are dimensions and cubes. Rather than two or three dimensions: row, column and sheet, the functional model supports as many dimensions as are ...
An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [2] 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.