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SQL/XML or XML-Related Specifications is part 14 of the Structured Query Language (SQL) specification. In addition to the traditional predefined SQL data types like NUMERIC, CHAR, TIMESTAMP, ... it introduces the predefined data type XML together with constructors, several routines, functions, and XML-to-SQL data type mappings to support ...
XML is stored into a native XML Type as defined by ISO Standard 9075-14 [6] RDBMS that support the ISO XML Type are: IBM DB2 (pureXML [7]) Microsoft SQL Server [8] Oracle Database [9] PostgreSQL [10] Typically an XML-enabled database is best suited where the majority of data are non-XML. For datasets where the majority of data are XML, a native ...
Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.
XQuery (XML Query) is a query and functional programming language that queries and transforms collections of structured and unstructured data, usually in the form of XML, text and with vendor-specific extensions for other data formats (JSON, binary, etc.).
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types. [14] Character strings and national character strings. CHARACTER(n) (or CHAR(n)): fixed-width n-character string, padded with spaces as needed; CHARACTER VARYING(n) (or VARCHAR(n)): variable-width string with a maximum size of n ...
XPath (XML Path Language) is an expression language designed to support the query or transformation of XML documents. It was defined by the World Wide Web Consortium (W3C) in 1999, [ 1 ] and can be used to compute values (e.g., strings , numbers, or Boolean values ) from the content of an XML document.
The Marburg virus, which causes bleeding from the eyes, nose, and mouth, can be fatal in up to 90% of those infected
An example of data mining that is closely related to data wrangling is ignoring data from a set that is not connected to the goal: say there is a data set related to the state of Texas and the goal is to get statistics on the residents of Houston, the data in the set related to the residents of Dallas is not useful to the overall set and can be ...