Learn: Data and Testing

Welcome!Hi! Building on what you've already learned about design tools and human-computer interfaces, today we'll explore how data is tested to ensure accuracy and reliability. Let's get started!

What is Data Testing?Data testing involves checking data to make sure it is correct, complete, and suitable for its purpose. It ensures that errors are found and fixed before the data is used.

Types of Data TestingThere are different types of testing for data:Validation: Checking if data meets specific rules (e.g., a phone number must have 11 digits).Verification: Ensuring that data has been entered correctly by comparing it with the original source.

Validation TechniquesValidation techniques include:Range checks: Ensuring numbers stay within a set range (e.g., age must be between 0 and 120).Format checks: Making sure data follows a specific format (e.g., email addresses must include '@').Presence checks: Confirming required fields are filled in.

Verification MethodsVerification involves comparing data entered into a system with the original source to ensure it is correct. Methods include:Double entry: Data is entered twice and compared.Proofreading: Data is manually checked against the original for errors.

Why Testing is Important?Testing ensures data integrity, which means the data is accurate, consistent, and reliable. Without testing, errors in data could lead to flawed decisions or system malfunctions.

Testing in Real LifeImagine a supermarket checking its stock levels. Validation ensures product quantities are realistic (e.g., no negative numbers), while verification checks that the entered stock matches the actual amount on shelves.

Review Time!Great work! You've learned about validation, verification, and why testing is essential. Now let's test your understanding with a few questions.

Well done!You've completed the lesson on Data and Testing. Keep practising to strengthen your understanding, and remember how important it is to ensure data is accurate and reliable!