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The BEFORE option does not allow you to modify tables, that is why input validation is a practical use. Using AFTER triggers allows you to modify tables such as inserting into an audit history table. Using AFTER triggers allows you to modify tables such as inserting into an audit history table.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
The set of query plans examined is formed by examining the possible access paths (e.g., primary index access, secondary index access, full file scan) and various relational table join techniques (e.g., merge join, hash join, product join). The search space can become quite large depending on the complexity of the SQL query. There are two types ...
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
Transform (clean, apply business rules, check for data integrity, create aggregates or disaggregates) Stage (load into staging tables, if used) Audit reports (for example, on compliance with business rules. Also, in case of failure, helps to diagnose/repair) Publish (to target tables) Archive
In SQL, a window function or analytic function [1] is a function which uses values from one or multiple rows to return a value for each row. (This contrasts with an aggregate function, which returns a single value for multiple rows.)
In computing, a materialized view is a database object that contains the results of a query.For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function.
SQL:2011 or ISO/IEC 9075:2011 (under the general title "Information technology – Database languages – SQL") is the seventh revision of the ISO (1987) and ANSI (1986) standard for the SQL database query language. It was formally adopted in December 2011. [1] The standard consists of 9 parts which are described in detail in SQL.