1. What problem can duplicated customer addresses create?
- Guaranteed faster correctness
- Automatic encryption
- Update anomalies
Check the answer and reasoning
Update anomalies
Updating one copy but not another can leave contradictory facts.
CS / AS level
Relational databases and normalisation
Relations connect records using primary and foreign keys. Entity relationships and normalisation reduce anomalies by assigning facts to appropriate tables.
Learning objectives
- Explain relational databases and normalisation using a concrete example.
- Apply the worked method and justify each step.
- Recognise the limitation described in the final check.
The big idea
Relations connect records using primary and foreign keys. Entity relationships and normalisation reduce anomalies by assigning facts to appropriate tables.
SQL selects, joins, groups and aggregates records. Distinguish filtering individual rows with WHERE from filtering aggregated groups with HAVING; a join needs a meaningful relationship condition.
Worked example
Orders.customer_id references Customers.id. Which is the foreign key?
Follow the solution
It links an order to a customer’s primary key.
Investigate and explain
Predict the worked result before calculating. Change one input, record the new result, and explain which assumptions still hold.
Use the prediction activity below; a local model appears only where it supports this topic.
Check your understanding
2. Orders.customer_id references Customers.id. Which is the foreign key?
- Orders.customer_id
- Customers.name
- Orders.total always
Check the answer and reasoning
Orders.customer_id
It links an order to a customer’s primary key.
3. Does normalisation mean deleting all repeated values?
- Yes
- No
- Only in SQL
Check the answer and reasoning
No
It organises dependencies; repeated foreign-key values may correctly represent many related records.