Organise tables to reduce redundancy.
Normalisation structures tables to remove redundancy and update anomalies: 1NF (atomic values), 2NF (no partial dependency), 3NF (no transitive dependency), BCNF. Denormalisation is sometimes used for read performance. Entity-relationship modelling guides the design.
Store customer address in a customers table, not in every order row.
Normalisation removes repeated data so that updates happen in one place, which prevents inconsistent records.
Organise tables to reduce redundancy.
Normalisation removes repeated data so that updates happen in one place, which prevents inconsistent records.
Each column holds atomic values and each row is unique, so there are no repeating groups within a row.
Not always. Some read-heavy systems deliberately denormalise to make queries faster, accepting more care in updates.
Typical applications include splitting a table that repeats customer addresses on every order into separate tables, removing duplicated product names from an inventory table and designing a database for a laboratory where readings link to samples and instruments.
Study "SQL queries and joins" first (topic 75 of 104 in Software & Computing). It covers the groundwork this topic builds on.
Functional dependencies. Keys. Trade-offs with performance.
Store customer address in a customers table, not in every order row.
The next topic is "Transactions and ACID", which builds directly on this one.
It is classed as Advanced in Software & Computing (topic 76 of 104). It is an advanced topic. It assumes you are comfortable with the intermediate topics in Software & Computing.
Want to practise? Open the interactive course for quick checks, quizzes, simulations and progress tracking.