Important Note

When setting up your .py file, this should be the structure:

from turtle import *

#all of your code goes here

mainloop()

Make sure you include the call to mainloop(). This is a built-in function and helps manage the window.

Database Normalizing

0NF → 3NF

When designing tables in a database, we need to ensure that the tables are normalized.

Normalization:

  • reduces data redundancy → prevents the same data being stored in multiple places, saving space and avoiding inconsistencies.
  • improves data integrity → ensures each fact is stored in one location, making updates accurate and reliable.
  • avoids update anomalies → prevents problems when inserting, deleting, or modifying records (e.g., losing important info when a row is deleted).
  • clarifies relationships → organizes data into logical tables with clear keys and links between them.
  • makes maintenance easier → simpler structure means queries, updates, and schema changes are easier to manage.

There are rules that govern these forms and in this unit we will consider the rules starting from unnormalized (0NF) all the way to third normal form, 3NF.

The following series of videos is intended to help introduce these concepts. For each video, complete the related worksheet.

  MMV
  MMV
  MMV

UNPLUGGED REVIEWS

Denormalized advantages

We have covered the importance of normalizing a database. It reduces data redundancy, decreases the opportunity for update/delete anomolies and improves data integrity generally.

In short, it will result in a reliable database.

But surely a denormalized database must have some advantages...

Advantage Description
Queries are simpler Without joins to consider, queries are simpler to design
Queries are faster Queries can be executed on one table, rather than navigating joins, making query-execution faster.
Less processing Because joins are not needed (or reduced), less processing power is required

Of course, in a denormalized database, there is a risk of:

  1. data duplication
  2. update/delete anomolies
  3. generally poor data integrity

However, in scenarios where a fast read is required, a denormalized database can out-perform a normalized database.

So when choose to normalize a database or leave it denormalized, the benefits will have to be weighed up against the drawbacks.

Normalizing

Normalizing a database reduces data redundancy. Data redundancy is where the same data is stored in multiple places in a database.

When updates occur, they have to update all of the data in all of the locations correctly.

Update anomolies refer to updates that don't do this, leading to inconsistent data.

Data redundancy also requires more storage space.

Data redundancy may, however, be intentional ie the database is storing a backup of the data.