Describe how a database organises data into tables, records and fields, explain the role of data types, primary keys, queries, sorting and validation, and outline the benefits of a database over a flat file.

What this dot point is asking

A database is software for storing large amounts of structured data so it can be searched, sorted and kept accurate. This part of Unit 1 expects you to describe how data is organised into tables, records and fields, explain data types, primary keys, queries, sorting and searching, and validation, and say why a database is better than an unstructured store. Databases sit behind almost every system you meet, from a school's pupil records to an online shop, so the vocabulary here recurs throughout the course.

Tables, records and fields

Data in a database is held in tables. A table is a grid, and the way it is divided up gives the three core terms you must know.

So a table of pupils has one record per pupil, and each record contains the same fields, such as Pupil ID, Forename, Surname, Date of Birth and Form. Reading down a column gives all the values of one field; reading across a row gives one complete record.

Data types and primary keys

Each field is given a data type that controls what kind of value it can hold and how it is stored. Common data types include text (for names and addresses), number (for quantities and prices), date or time, and Boolean (a yes/no or true/false value). Choosing the correct data type keeps data consistent and lets the database sort, calculate and validate correctly; for example, storing a date as a date type allows it to be sorted into chronological order and used in age calculations.

The primary key matters because it guarantees that records can always be told apart, even when other fields hold the same values, and it is used to link tables together in larger databases.

Searching, sorting and querying

The power of a database is how quickly it finds and organises data.

A query searches the database and returns only the records that meet stated criteria, for example all customers who live in Belfast, or all orders placed after a given date. Sorting arranges records into order on a chosen field, such as alphabetical by surname or by price from low to high. Together, querying and sorting let a user pull out and present exactly the information they need from a very large store.

Validation and verification

Keeping the data accurate is essential, and two different processes help.

Validation is an automatic check that data is sensible and follows the rules before it is accepted. Common validation checks are a range check (a number lies between limits, such as an age from 0 to 120), a presence check (a required field is not blank), a format check (data matches a pattern, such as a postcode), a length check (the right number of characters, such as a phone number) and a type check (the value is the correct data type, such as a number). Verification is checking that data has been entered correctly and matches the original source, for example by typing a password twice or proofreading against a form.

The crucial difference is that validation checks data is reasonable, while verification checks it is accurate. Validation cannot catch a sensible but wrong value: a correctly formatted but incorrect date of birth passes validation, so verification is still needed.

Why this matters

Databases are how organisations store and manage information at scale, and the same structure underlies the database practical work and links to data protection, where personal data must be kept accurate and secure. Understanding fields, records, keys, queries and validation lets you reason about almost any information system you meet in the unit.