Data and Information
Core concepts
This domain is about the difference between data (raw symbols) and information (data processed into meaning). Candidates must understand the data information cycle: collection, organisation, storage, processing, analysis, presentation and interpretation, and be able to identify where errors can enter.
Know data types (integer, real/float, boolean, character, string, date/time) and why choosing the correct type matters for storage and validation. Understand validation (is the input reasonable?) versus verification (is the data an accurate copy of the source?), with techniques such as range checks, type checks, presence checks, length checks, format checks and check digits, plus double-entry verification.
Relational database concepts are examinable: tables, records, fields, primary keys, foreign keys, relationships (one-to-one, one-to-many, many-to-many) and the purpose of normalisation in reducing redundancy and inconsistency. You should be able to read and write simple SQL (SELECT, FROM, WHERE, ORDER BY) and understand basic query logic. Also know structured versus unstructured data, and simple data visualisation choices.
Traps
- Saying validation guarantees correctness; it only checks acceptability. Verification addresses accuracy.
- Confusing a primary key (unique identifier in its own table) with a foreign key (references another table's primary key).
- Assuming normalisation removes all duplication; it removes harmful redundancy, not every repeated value.
- Selecting the wrong chart type (pie charts for many categories, line charts for non-sequential data).
- Forgetting that a many-to-many relationship requires a linking table.
Worked example
Query: SELECT name FROM students WHERE year = 11 ORDER BY name; This returns only the name field, filters records, then sorts alphabetically. Rule of thumb: read a query in the order FROM → WHERE → SELECT → ORDER BY, even though it is written differently.