Data Validation: The What, Why, and How

Data validation is a technique used to ensure that data imported or fed into a system meets specific quality and integrity standards. It involves creating criteria for data input and displaying warnings with error messages if the user inputs data that fails to meet these criteria. Validation enhances data reliability, accuracy, and security by preventing the input of invalid data and reducing the need for manual checks while saving time for cleaning bad data. Some best practices for effective data validation include using consistent rules, keeping validation rules simple, automating repetitive tasks, and validating data in real-time as close to the source as possible. Data validation is crucial in various industries such as healthcare, financial services, retail, and high-tech, where it helps maintain accurate records, detect fraudulent activities, create personalized shopping experiences, and prevent malware introduction. Common data validation techniques include range checking, format checking, consistency checking, uniqueness checking, completeness checking, presence checking, and code checking.