DATA VALIDATION RULES (GENERAL)

data validation rules:

1. Required Fields:
   

   • Description: This rule ensures that certain fields must be filled out.

   • Example: In an online shopping cart, the "Billing Address" field is marked as required. The user cannot proceed with the checkout process without providing a billing address.

1. Numeric Range Validation:
   

   • Description: Validates that numeric values fall within a specified range.

   • Example: In a student grading system, the "Grade" field must be between 0 and 100. Any value outside this range is considered invalid.

1. Email Format Validation:
   

   • Description: Ensures that email addresses are entered in a valid format.

   • Example: In a user registration form, the email field is validated to ensure it follows the pattern user@example.com.

1. Unique Key Constraints:
   

   • Description: Enforces that a specific field or combination of fields must be unique.

   • Example: In a database of user accounts, the "Username" field must be unique. No two users can have the same username.

1. Length Validation:
   

   • Description: Checks if the length of a field is within a specified range.

   • Example: In a password field, the user's password must be at least 8 characters long but no more than 20 characters.

1. Regular Expressions (Regex):
   

   • Description: Uses pattern matching to validate data against a specific pattern or format.

   • Example: Validating a U.S. Social Security Number using the pattern ###-##-####.

1. List or Dropdown Validation:
   

   • Description: Ensures that a selected value from a list or dropdown is valid and allowed.

   • Example: In a web form for selecting a country, the user can only select from a predefined list of countries.

1. Consistency Validation:
   

   • Description: Compares data across different fields to ensure consistency.

   • Example: In a booking system, the "Departure Date" must be after the "Arrival Date" to be considered valid.

1. Business Rule Validation:
   

   • Description: Applies custom rules specific to the business domain.

   • Example: In an e-commerce platform, a "Free Shipping" promotion may require a minimum order amount of $50 to be valid.

1. Pattern Matching Validation:
   

   • Description: Verifies that data follows a specific pattern or structure.

   • Example: Validating credit card numbers using the Luhn algorithm to ensure they have a valid structure.

These are just a few examples of data validation rules. Depending on the context and the specific requirements of a system or application, additional validation rules may be implemented to ensure data integrity and accuracy.