Within most things in life people get things wrong which makes things break, become incorrect or even corrupted, and there is no exception for databases. I am going to talk about the fairly common errors within a database that happen and how you can overcome these errors with simple steps.
Accidental deletion of fields
When a database is in use, you may find it really easy to accidently delete data which could mean allot of stress. One main way to avoid this would be to make sure that back-ups are made of the data, so whatever the matter the data will not be completely lost. However, it is very annoying when data becomes deleted because it takes allot of time and effort to retype the data. The best way to stop accidental deletion is to set the database to only the designer can manipulate it, so anyone using the database without authorisation cannot manipulate and is only able to read the database with no risk of deletion.
Incorrect data types
Incorrect data type issues can occurs when an unmatched data type is used. An example would be, a field called ‘fees’ in a table in a database, it will go wrong is a ‘text value’ is inserted instead of a ‘numerical value’ like ‘two hundred’ instead of ‘200’. This can be avoided as you can tell the database to only allow numerical values to be inputted within that field so this error won’t accrue again. The database won’t allow anything inputted other than numbers.
Renaming something or someone incorrectly on a database can be a huge mistake, hugely if it were to happen to be a bank. This is mostly done by human error as a typo or misheard information. This means if the error isn’t spotted then it will not be sorted out; so a way to sort out the problem is by double checking the information given and typed.
Validation within computers is on par with people verification checks, but checks the data to see if the data entered is sensible and reasonable. When a user puts information in to a database which might not be right then the computer will do validation checks to see a match between the users input and information given to the database to run though a list of checks. Here is an example: The database is given a set of rules to run by which would be ;=18 which means that nothing under the number (age) is allow to carry on to the next step. So if someone that is the age of 17 or under will not be allowed to move forward. So as you can see this helps to validate information allowing and disallowing data which helps to organise the database making sure all the data is correct.
The meaning of a null value equals to “nothing there” within a database. This would be a big problem with the database as the database will not be able to work properly as it doesn’t understand what it is told and might cause other errors within the database. If the data base has not been set to understand the null values it would carry on to the next step, but to prevent this from happening you can the use of a validation rule. The validation rule will work to stop the null value from happening like in an ‘online application form’ where if no value were to be entered then a user wouldn’t be able to carry on to the next step; the validation rule will work in the same way to stop the null value from accruing and missing values from happening.