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The database persists data that your application (and organization) depends on. The data thus persisted is most often of mission-critical nature and a key asset for the organization. Also, many of today's data-enabled applications implement a fair amount of their functionality and business logic in the database itself. For an enterprise class application, the data in the database would be accessed and updated (insert/modify/delete) simultaneously by a large number of users (think thousands to millions depending on the scale of your application's usage).
The above statements highlight a few areas where database testing is needed. One, to validate the quality of data being persisted. Two, if we plan to test the application code, it is imperative that we also test the code in the database which implements the business functionality and three, we should plan for non-functional database testing to support the usage of the database in a real-world deployment scenario.
Let us briefly look at the above mentioned database test areas.
1. Data quality testing
Testing the quality of the data may be approached in three ways - data validity testing, data integrity testing and data format testing.
a) Data validity testing - is done to verify the validity of the data that is stored in the database. When data is entered via the front end application, check if the data is correctly updated in the back-end database. Apart from the positive checks, look for other behavior such as data truncation, verify how null/empty field values are handled, verify how special characters or code snippets are handled in the database. Check that the right columns in the right tables are being updated. Data validity testing normally involves use of SQL queries to validate the data.
The above statements highlight a few areas where database testing is needed. One, to validate the quality of data being persisted. Two, if we plan to test the application code, it is imperative that we also test the code in the database which implements the business functionality and three, we should plan for non-functional database testing to support the usage of the database in a real-world deployment scenario.
Let us briefly look at the above mentioned database test areas.
1. Data quality testing
Testing the quality of the data may be approached in three ways - data validity testing, data integrity testing and data format testing.
a) Data validity testing - is done to verify the validity of the data that is stored in the database. When data is entered via the front end application, check if the data is correctly updated in the back-end database. Apart from the positive checks, look for other behavior such as data truncation, verify how null/empty field values are handled, verify how special characters or code snippets are handled in the database. Check that the right columns in the right tables are being updated. Data validity testing normally involves use of SQL queries to validate the data.
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