Shree Secondary School

Before we start investigating the complexities involved in implementing data integrity constraints using database triggers, we will first introduce a classification schema for data integrity constraints. Agreeing upon a classification scheme for constraints, helps us a lot in implementing them: for we can then approach the problem area on a class-by-class basis. A classification scheme needs to have a few properties: 1.      The constraint classes should be   mutually exclusive : any given constraint should clearly fall into one, and only one, of the classes; 2.      The scheme should   cover all types of constraints : i.e. it cannot be that we can think of a constraint that doesn't fall into one of the defined classes; 3.      It should   be practical : and by this we mean it should help us when implementing constraints. Or, put in another way, the issues we have when implementing constraints of the ...

Data integrity   refers to maintaining and assuring the accuracy and consistency of   data   over its entire   life-cycle ,   and is a critical aspect to the design, implementation and usage of any system which stores, processes, or retrieves data. The term   data integrity   is broad in scope and may have widely different meanings depending on the specific context – even under the same general umbrella of   computing .   Data integrity is the opposite of   data corruption , which is a form of   data loss . The overall intent of any data integrity technique is the same: ensure data is recorded exactly as intended (such as a database correctly rejecting mutually exclusive possibilities,) and upon later retrieval, ensure the data is the same as it was when it was originally recorded. In short, data integrity aims to prevent unintentional changes to information. Data integrity is not to be confused with   data security ...

Database is an organized collection of data that can be accessed as according to the user.