Information, Data Types & Validation
Data and Information — Not the Same Thing
Students often use the words “data” and “information” as if they mean the same thing. They do not. Data is raw, unprocessed facts — numbers, letters or symbols that mean nothing without context. Information is data that has been processed and given meaning.
The key step is processing. Take the raw numbers 17, 19 and 22: on their own they are meaningless data. Process them — calculate the average, attach labels and a date — and you get the useful statement: “The average daily temperature in Manchester this week was 19°C.” This distinction matters on the exam: an answer that simply says the numbers are “information” without describing the processing step will lose a mark.
Data is raw, unprocessed facts (e.g. “17, 19, 22”). Information is data that has been processed and given context to make it meaningful. Processing is the step that converts one into the other.
Data Types
Choosing the correct data type is essential when designing any IT system. The five main data types are alphanumeric, Boolean, date, numeric and text. Each has specific characteristics that make it suitable for different kinds of data.
Alphanumeric combines letters and numbers — ideal for postcodes (SW1A 1AA), reference numbers (INV-2024-001) and registration plates. Boolean stores only two values: true or false (or yes/no, 1/0). It suits any yes/no field, such as whether a customer has agreed to marketing emails. Date stores date values in a consistent format (e.g. DD/MM/YYYY) and allows date-based calculations such as working out how many days until an order is due.
Text stores any string of characters without treating them as numbers — used for names, addresses and descriptions where calculation is not needed. Numeric covers several sub-types: integer (whole numbers, e.g. quantity in stock), real or decimal (numbers with a decimal point, e.g. 4.99), currency (formatted decimal, e.g. £4.99), and percentage (a decimal expressed as a percentage, e.g. 12.5%).
Validation is an automated check that data is reasonable and in the right format. It happens automatically as the user types or submits a form. For example, a validation rule might check that an age field contains a number between 0 and 120.
Crucially, validation cannot check whether data is true. If someone enters their age as 25 when they are actually 30, the validation rule accepts the value — it is a plausible number. Validation only catches data that is impossible or implausible.
Verification checks that data has been entered correctly by comparing it against the original source. The two verification methods are double entry (asking the user to type the same data twice, e.g. confirming a password) and manual checking (a person compares printed output against the original document). Verification catches transcription errors that validation cannot detect.
Data Validation Tools
There are nine named validation tools. A data type check ensures the entry matches the expected data type (e.g. rejects letters in a numeric field). A format check tests that data follows a specific pattern — for example, an input mask for a UK postcode can require a pattern such as AA9A 9AA. A length check ensures the entry is not too short or too long (e.g. a PIN must be exactly 4 digits).
A limited choice tool restricts the user to a predefined set of values. This includes drop-down lists (the user selects from a visible list), radio buttons (the user selects one option from a small set) and tick lists (the user checks one or more boxes). A lookup checks that the entry exists in a reference table — for example, checking that a customer ID exists in the customer database before an order is placed. A presence check ensures a required field is not left blank. A range check ensures a numeric value falls within acceptable limits (e.g. exam scores must be between 0 and 100).
Exam questions often give a scenario (e.g. a hospital booking system) and ask you to justify a data type or validation tool for a specific field. Work through the field’s purpose: does it store numbers used in calculations? Use a numeric type. Does it need a specific pattern? Use a format check or input mask. Is it a yes/no field? Use Boolean. Must it come from a fixed list? Use a drop-down list or radio buttons.
Remember: validation is automatic (built into the form), verification is a human or repeated-entry check. A hospital patient’s date of birth field would use a date data type, a format check to enforce DD/MM/YYYY, a range check to ensure it is not in the future, and might use double entry (verification) to confirm the nurse typed it correctly.
The nine validation tools are: data type check, format check, input mask, length check, limited choice (drop-down list / radio buttons / tick list), lookup, presence check and range check. These can appear in any exam scenario question.