Data integrity refers to the accuracy and consistency of data stored in a database or other data storage system. It ensures that the data in the system is reliable, accurate, and consistent over time.
How is data integrity maintained?
Data integrity is maintained by enforcing data validation rules, referential integrity constraints, and other data integrity rules in the database.
These rules help to ensure that data is entered correctly and that it meets certain quality standards.
For example, a data validation rule might require that a date field in a database be entered in a specific format, such as YYYY-MM-DD, to ensure that all dates are entered consistently.
What is referential integrity?
Referential integrity constraints are used to ensure that relationships between tables in a database are maintained properly.
For example, a referential integrity constraint might ensure that a customer record cannot be deleted if it is associated with an order in another table.
Other data integrity rules might include constraints on data types, such as requiring that a field contain only numeric data, or constraints on data ranges, such as requiring that a date field falls within a certain range.
How is data integrity essential?
Overall, data integrity is essential for ensuring that the data in a database is reliable and accurate.
It helps to ensure that data is entered consistently and that relationships between data in different tables are maintained properly.
This, in turn, helps to ensure that the results of queries and other data analysis processes are accurate and trustworthy.