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Pages in category "Articles with example SQL code" The following 28 pages are in this category, out of 28 total. This list may not reflect recent changes. A.
The following is an Oracle syntax example of a row level trigger that is called AFTER an update FOR EACH ROW affected. This trigger is called on an update to a phone book database. When the trigger is called it adds an entry into a separate table named phone_book_audit.
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.)
Software validation checks that the software product satisfies or fits the intended use (high-level checking), i.e., the software meets the user requirements, not as specification artifacts or as needs of those who will operate the software only; but, as the needs of all the stakeholders (such as users, operators, administrators, managers ...
After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.
Correlated subqueries may appear elsewhere besides the WHERE clause; for example, this query uses a correlated subquery in the SELECT clause to print the entire list of employees alongside the average salary for each employee's department. Again, because the subquery is correlated with a column of the outer query, it must be re-executed for ...
In evaluating the basics of data validation, generalizations can be made regarding the different kinds of validation according to their scope, complexity, and purpose. For example: Data type validation; Range and constraint validation; Code and cross-reference validation; Structured validation; and; Consistency validation
A real-life ETL cycle may consist of additional execution steps, for example: Cycle initiation; Build reference data; Extract (from sources) Validate; 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 ...