Activity Solutions

1. Budget Calculator

2. Step Counter App

3. Quiz App

Activity 1

• Ask the user to enter homework details (subject, task, due date)

• Store the homework tasks in a list or file

• Display the list of tasks to the user

• Allow the user to mark tasks as completed

• Sort or filter tasks by due date or subject

Activity 2

• Get team names and store them

• Set the starting score for each team to zero

• Create a way to add or subtract points during the game

• Display the current score on screen

• Show a final message with the winner when the game ends

Activity 3

• Load a set of questions and multiple-choice answers

• Display one question at a time to the user

• Record the user’s selected answer

• Check if the answer is correct and keep score

• Show the final score after all questions are answered

Activity 1

Quiz Feedback Program:

• Each question has a structure: question text, multiple options, one correct answer

• The same process is repeated: show question → get answer → check answer → give feedback

• Feedback messages follow a pattern (e.g. “Correct!” or “Incorrect, the right answer is...”)

Activity 2

Weather App:

• Each day’s forecast uses the same data format: day name, icon, temperature, description

• Icons represent weather types (e.g. sun, cloud, rain) and are reused across days

• Patterns in temperature changes (e.g. hot in afternoon, cool at night) can be recognised

Activity 3

Timetable Generator:

• Class times follow regular patterns (e.g. Period 1 starts at 9:00 every day)

• Subjects repeat on the same days each week

• Breaks and lunch are placed in the same time slots across all timetables

Activity 1: Water Intake App

• Necessary information and features: Date, amount of water consumed, daily goal, total intake so far, and a simple way to log each drink

• Unnecessary details to leave out: Brand of water, exact time of each sip, detailed drink history beyond a few days

• Abstraction used: Focus on tracking totals and goals; ignore details that don’t help the user meet their target

Activity 2: Puzzle Game

• Parts that stay the same: Player controls, puzzle-solving mechanics, scoring system, level completion logic

• How to group/simplify: Use a single function or module to handle shared game mechanics; only change artwork, sound, and puzzle layout per level

• Abstraction used: Group repeated behaviour into reusable procedures or objects (e.g. movePlayer(), checkPuzzleComplete())

Activity 3: Staff Profiles Website

• Essential information: Name, photo, job title, email address

• How to keep it consistent: Use one profile template or function that fills in staff data for each person

• Abstraction used: Create a reusable layout or function for all staff profiles instead of writing separate code for each one

Activity 1: School Attendance App

Parts of the system:

• Student data input (e.g. scanned ID or manual entry)

• Database storing attendance records

• Notification system for sending updates to teachers and parents

• Reporting interface for staff

Interactions:

• When a student is marked present or absent, the database updates

• The system sends notifications based on changes

• Reports are generated from stored attendance data

• If the input method fails, notifications and reports may be incorrect

Activity 2: Online Food Delivery System

Parts of the system:

• User app (for browsing and ordering)

• Restaurant system (receives and confirms orders)

• Payment gateway

• Delivery tracking system

Interactions:

• The user order triggers updates across the system

• Payment confirmation activates the restaurant system

• Restaurant status affects delivery time

• If one part fails (e.g. restaurant delay), it affects the whole order process

Activity 3: Smart Home Lighting System

Parts of the system:

• Light bulbs or smart switches

• Sensors (e.g. motion or daylight sensors)

• User interface (e.g. mobile app or voice assistant)

• Automation rules

Interactions:

• Sensor input affects lighting behaviour

• User settings control when and how lights change

• Automation rules link actions together (e.g. turn off lights when no motion)

• A change in settings or sensor failure can disrupt the whole system’s function

Here are the answers to the algorithm learning questions:

1. Algorithms are the set of commands or instructions that tell a computer what to do and how to solve a problem.

2. It processes instructions one after the other in the order they appear.

3. Assignment stores the result of an expression into a variable, which holds the value for later use in the program.

4. A condition checks whether something is true or false; selection uses that condition to decide if a part of the code should run.

5. Iteration repeats a set of instructions multiple times, while sequence runs instructions once, in order.

6. Example: A guessing game where the computer checks if your guess is correct (selection), and keeps asking until it is (iteration).

7. It makes programs easier to manage, test, reuse, and debug by breaking them into smaller, logical sections.

8. Sequence (to go through questions), selection (to check answers), assignment (to store score), iteration (to go through multiple questions), and possibly modularisation (to separate the quiz logic into functions).

9. The code could become hard to read, debug, test, and maintain. Errors in one part of the code may affect other parts.

1. To store values in computer memory for use in a program.

2. The kind of data stored at that memory location.

3. Dynamic types are checked at runtime and can change; static types are checked before running and cannot change.

4. Because type checking happens at runtime and variables can change type.

5. With single or double quotes.

6. int

7. float

8. True and False

9. Values that evaluate to True or False in a Boolean context.

10. None, 0, ''

11. Falsy

12. Where in the program a variable can be used.

13. Global is defined outside functions and used anywhere; local is defined inside functions and used only there.

14. It limits variable access to reduce bugs and improve code organisation.

15. Local, Enclosing, Global, Built-in

16. Local → Enclosing → Global → Built-in

17. It overrides the built-in function while the code runs.

18. No

19. No

20. Global variables and built-in names

1. Sequential, selection, iteration

2. Line by line from top to bottom

3. A check to see if something is true or false

4. True or False

5. if and while

6. value operator value

7. !=

8. >=

9. Choosing a path in code based on a condition

10. Branching

11. It checks conditions in order and runs the first block that is true

12. Yes

13. Nothing runs unless there’s an else block

14. Runs if all previous conditions are false

15. Compares a variable against fixed values

16. Python 3.10

17. Repeating a block of code

18. Loop

19. Definite has a known number of repetitions; indefinite does not

20. for loop

21. while loop

22. Post-test loop (do...while)

23. while loop

24. Uses each item one at a time

25. A container you can move through one item at a time

26. Lists, tuples, strings (also: dictionaries, sets)

1. To store data in an organized form.

2. As collections of related data, like a shopping list or contact list.

3. Lists, tuples, sets, dictionaries.

4. An ordered collection of items.

5. Using square brackets [] with items separated by commas.

6. Items can be changed, added, or removed.

7. Index 0.

8. Tuples cannot be changed (immutable), lists can.

9. They offer faster performance and are ideal for fixed data.

10. Using parentheses () with items separated by commas.

11. A collection of unique items with no specific order.

12. Sets are unordered and only hold unique items.

13. Yes.

14. When you only care about whether an item exists, not order or duplicates.

15. Key-value pairs.

16. Using curly braces {}, with a colon : between each key and value.

17. Keys must be unique.

18. Yes.

19. The rules a programming language follows to write commands properly.

20. It ensures commands are written in a valid way that Python can understand.

1. A class is a blueprint for creating objects.

2. Attributes and methods.

3. An attribute stores data in a class.

4. A method performs an action in a class.

5. colour, wheels

6. drive(), brake()

7. To define shared structure and behaviour for multiple car objects.

8. By calling the class name with parentheses, e.g. Car()

9. It creates a new object called ferrari from the Car class.

10. It allows shared code to be reused without repetition.

11. Repeating code.

12. It calls the drive() method on the ferrari object, passing distance as a value.

13. Because they have similar features but also differences.

14. Objects are created from classes and follow their structure.

15. In the Deepest Dungeon course.

1. To perform actions on variables or values.

2. Arithmetic, assignment, comparison (others: logical, identity, membership, bitwise).

3. Perform basic maths with numbers.

4. Addition.

5. Whole number result of dividing x by y (floor division).

6. Control the order of operations, like in maths.

7. Exponentiation (power).

8. Assign or update the value of a variable.

9. Add 3 to the current value of x.

10. = sets a value; += increases the value by adding.

11. True or False.

12. Checks if two values are not equal.

13. True

14. Returns True if both conditions are True.

15. Reverses the result of the condition x < 5.

16. True (since x < 5 is true).

17. Whether two variables are the same object in memory.

18. Returns True if x and y refer to the same object.

19. True

20. If a value exists in a sequence like a list or string.

21. True

22. When you want to check that a value is not in a sequence.

23. True

1. Dependable code runs consistently under different conditions, handles errors gracefully, and avoids crashes, building user confidence and trust.

2. It helps others (or your future self) quickly understand, fix, or improve the code without breaking other parts.

3. Lower cognitive load makes the code easier to follow, reducing errors and making updates or collaboration simpler.

4. A dependency chain is when one module relies on another. Changes in any linked module can cause unexpected bugs or break the program.

5. Small functions are easier to test and debug. Good names and comments explain what code does, making it easier to work with.

6. Consistent style improves readability and helps teams follow the same structure, reducing mistakes and confusion.

7. It allows you to write code that handles invalid input or failures safely, preventing crashes and improving user experience.

8. Testing finds errors before users do, making sure the program behaves correctly and consistently.

9. Clear names show what variables or functions do, helping all team members quickly understand and use the code correctly.

10. Handling edge cases avoids unexpected crashes or bugs, making the program more robust and user-friendly.

1. Efficiency means completing tasks using the least amount of time and processing power.

2. The right data structure makes it faster to store and access data, improving speed.

3. Unnecessary steps slow down programs and waste resources.

4. Some algorithms use fewer steps to get to the solution, making them faster.

5. Nested loops take more time because they run many times for each outer loop run.

6. Small functions are easier to test, update, and reuse, making code faster and simpler.

7. Your code should still perform well even as the data grows; it should use minimal time and memory.

8. Code efficiency is about reducing resource use, which supports the speed and structure of algorithmic efficiency.

9. A for loop avoids repetition and runs faster than many repeated if-then-else checks.

10. Clear and simple code is easier to read and less likely to have mistakes that slow it down.

11. Functions reduce repeated code, making updates easier and programs more efficient.

12. Storing repeated results saves time by avoiding recalculating the same thing.

13. A dictionary is faster than a list for lookups because it finds items using keys.

14. Testing with different data sizes helps you find ways to make code faster and use fewer resources.

1. Effectiveness measures how well an algorithm solves the intended problem.

2. Understanding the problem clearly ensures the solution is accurate and relevant.

3. Success criteria help you check if the solution works, like producing the correct output or meeting user needs.

4. Breaking the problem into smaller steps makes it easier to design and manage the algorithm.

5. Pseudocode or flowcharts help plan the logic before coding, reducing mistakes.

6. Clear and structured logic makes code easier to follow and less likely to have errors.

7. Testing with real, edge case, and invalid data ensures the algorithm handles all situations correctly.

8. If the algorithm doesn’t work as expected, refine or fix it based on what you learned from the results.

9. User or tester feedback can show issues or improvements you didn’t notice, helping you make a better solution.

10. A desk check can work for simple problems, but complex problems need real testing to see if they function in all conditions.

1. The main purpose of testing is to check that code performs as expected.

2. Testing helps ensure the solution solves the problem (effective), runs smoothly (efficient), and works reliably (dependable).

3. Testing should occur throughout development to catch and fix issues early and improve quality over time.

4. Exploratory testing is informal testing done by trying features without a set plan.

5. Exploratory testing helps spot unexpected issues and ensures the solution feels usable and effective.

6. Unit testing focuses on checking individual parts of code, such as functions or classes.

7. Unit testing improves dependability by catching errors close to where they occur.

8. Integrated testing checks how different components of the program work together.

9. Integrated testing is important because some problems only appear when parts of the system interact.

10. Using all three types of testing helps make the solution more reliable, accurate, and high-performing.

1. Debugging is finding and fixing errors (bugs) in a program so it works correctly.

2. Bugs can cause crashes, unexpected behaviour, or incorrect results.

3. Python runs line-by-line, so one error can stop the whole program from continuing.

4. VSCode provides breakpoints, step controls, variable and watch panels, and a call stack viewer.

5. Click the “Run and Debug” tab, then select “Run and Debug” and choose “Python File.”

6. A breakpoint pauses the code on a specific line; set one by clicking next to the line number.

7. The “Variables” panel shows the current values stored in variables while the program is paused.

8. “Step Over” runs the current line and moves to the next line in the same function.

9. “Step Into” enters a function call to let you debug inside that function.

10. “Step Out” runs the rest of a function and returns to where it was called.

11. Conditional breakpoints only pause when a set condition is true, helping catch specific errors.

12. An example is y == 0, which pauses the code only when y equals zero.

13. You can change variable values while paused to test scenarios or fix bugs on the fly.

14. The watch panel lets you track expressions or values as the program runs.

15. The call stack shows the order of function calls leading to the current line.

16. Print-based debugging is helpful for quick checks or when you’re unsure where the bug is.

17. Breakpoints pause the program, and the variables panel shows what’s happening at that moment.

18. Install the Python and Python Debugger extensions in VSCode.

19. Testing different values while paused helps understand bugs or test fixes without restarting.

20. These tools help spot issues earlier, understand program behaviour, and fix bugs faster.

1. Error correction is the process of finding and fixing mistakes in code so the program runs correctly.

2. Developers get better at spotting and fixing errors through regular coding and experience.

3. The three main types of errors are syntax errors, runtime errors, and logic errors.

4. Syntax errors happen when the code doesn’t follow the rules of the Python language.

5. Syntax errors must be fixed before running the program because they stop the program from starting.

6. IDEs usually highlight syntax errors to help developers find and fix them quickly.

7. Common syntax errors include misspelled commands, undeclared variables, and missing brackets.

8. Runtime errors occur while the program is running, usually causing it to crash.

9. Dividing by zero causes a runtime error and stops the program.

10. Adding a number and a string causes a runtime error because they are incompatible types.

11. A runtime error happens if you try to access an index in a list that doesn’t exist.

12. Logic errors happen when the program runs but gives the wrong result or behaviour.

13. A logic error doesn’t crash the program, but it causes incorrect output or actions.

14. Using the wrong condition, like < 5 instead of <= 5, can lead to incorrect program logic.

15. Misplaced brackets or incorrect operations can cause logic errors in calculations.

16. Reusing variable names incorrectly can cause unexpected results or overwrite important data.

17. An unintended infinite loop causes the program to keep running without stopping.

18. Using Boolean operators incorrectly can change the meaning of a condition and cause logic errors.

19. Using a variable before it’s declared results in a syntax error.

20. Poor program design can lead to logic errors because the structure of the code doesn’t match the intended logic.

1. Code simplicity means writing code that is easy to read and understand.

2. Clear logic and meaningful names make code easier for others (and your future self) to follow.

3. Simple code is easier to work with, reducing mistakes and making it easier to improve.

4. Python naming rules require names to use only letters, numbers, and underscores, with no spaces, and not start with a number.

5. Variable names can’t start with a number because it breaks Python’s syntax rules.

6. Case-sensitive means name and Name are treated as different variables in Python.

7. Naming rules must be followed to run code, while naming conventions help others understand it.

8. temperature_celsius clearly describes what the value represents, while x gives no context.

9. snake_case uses lowercase letters and underscores, and it’s used for variables and functions.

10. Constants should be written in UPPER_CASE with underscores, like MAX_SIZE.

11. CamelCase capitalises each word without underscores and is used for class names.

12. Python keywords have special meanings, so using them as variable names causes errors.

13. Comments are needed when code is complex or not immediately clear, even with good names.

14. A docstring is placed right after a function definition and explains what the function does.

15. A docstring should describe the function’s inputs, processes, and outputs.

16. IDEs use docstrings to show help messages, hints, and tooltips while coding.

17. Block comments explain specific sections of code that may be hard to understand at a glance.

18. They help other readers understand why a certain piece of code works the way it does.

19. Code portability means the same code works on different systems without changes.

20. Python is portable because it runs on many platforms like Windows, macOS, Linux, iOS, Android, and the web.

Refactored booking_system.py

Refactored version of the booking_system.py file that follows good programming practices and addresses all activity tasks:

import os

def clear_screen():
    """Clears the terminal screen in a cross-platform way."""
    os.system("cls" if os.name == "nt" else "clear")


def is_valid_seat(seat_number):
    """Returns True if seat number is between 0 and 50."""
    try:
        seat = int(seat_number)
        return 0 <= seat <= 50
    except ValueError:
        return False


def collect_bookings():
    """
    Collects booking information from users.

    Returns:
        list: A list of bookings in the format [(name, seat_number), ...]
    """
    bookings = []

    while True:
        name = input("Enter your name: ").strip()
        if not name:
            print("Name cannot be empty.")
            continue

        seat = input("Enter seat number (0–50): ").strip()
        if not is_valid_seat(seat):
            print("Invalid seat number.")
            continue

        bookings.append((name, seat))
        more = input("Add another booking? (y/n): ").lower().strip()
        if more == "n":
            break

    clear_screen()
    return bookings


def show_bookings(bookings):
    """Prints all collected bookings to the screen."""
    print("Your Bookings:")
    for booking in bookings:
        print(f"{booking[0]} - Seat {booking[1]}")


def main_menu():
    """Displays the main menu and handles user choices."""
    while True:
        print("Cinema Booking System")
        print("1. Book a Seat")
        print("2. Exit")
        choice = input("Enter choice: ").strip()

        if choice == "1":
            bookings = collect_bookings()
            show_bookings(bookings)
        elif choice == "2":
            print("Goodbye!")
            break
        else:
            print("Invalid option. Please try again.")


if __name__ == "__main__":
    main_menu()

Summary of Fixes

Style and Naming Issues:

• Changed function and variable names to follow snake_case

• Added clear, descriptive names

• Followed PEP 8 for formatting

Maintainability Issues:

• Broke up long and unclear code into small, single-purpose functions

• Added docstrings and block comments

• Removed hardcoded platform-specific logic from main functions

Efficiency Problems:

• Removed repeated input validation logic

• Used return values and parameters to pass data cleanly between functions

Testing Plan Example

1. Inheritance – it lets Car reuse the code from Vehicle, reducing repetition and improving structure.

2. MVC pattern – separates data (Model) from display (View), making the app easier to manage and update.

3. Event-driven programming – event handlers respond to user actions like clicks or key presses.

4. One is working on the View, the other on the Model – MVC allows both to work independently without conflict.

5. Event handler – triggered by the event loop when the key press is detected.

6. Object-Oriented Programming (OOP) – allows the use of classes and objects to model shared and unique behaviours.

1. User Experience (UX) refers to the overall experience a person has when interacting with a digital product, including how easy it is to use, how efficient and satisfying the experience is, and whether it meets the user’s needs and expectations.

2. User-first design is important because it ensures the solution meets the needs of the people using it, while developer-first or machine-first design can lead to frustration and poor usability.

Activity 1

Examples of Alignment on the LEGO Website:

• Top Navigation Bar: Menu items like “Shop,” “Discover,” “Help,” and the search and cart icons are horizontally aligned, creating a clean and organized header.

• Product Grid Layout: On category pages, products are aligned vertically in columns and horizontally in rows, making it easy to scan and compare items.

• Homepage Banners: Promotional text and buttons are aligned with images or backgrounds. For example, text is often left-aligned or centred depending on the layout, maintaining visual consistency.

• Footer Links: Links in the footer are aligned into neat columns under headings like “About Us,” “Support,” and “Legal,” allowing for quick navigation and readability.

• Text Blocks and Images: On product pages, text descriptions, prices, and buttons are left-aligned with the product image, ensuring a coherent flow of information.

Examples of Balance on the LEGO Website:

• Homepage Hero Sections: Large feature images are visually balanced with text boxes or call-to-action buttons placed on the opposite side, achieving symmetrical or asymmetrical balance.

• Product Pages: Images on the left and product information (name, price, reviews, buttons) on the right create a balanced layout that guides the user’s attention naturally.

• Category Pages: Products are evenly spaced in a grid format, ensuring visual weight is distributed across the screen, maintaining consistent spacing and size.

• Navigation and Icons: The logo, navigation menu, and icons (search, cart, account) are placed to balance each other across the top bar, preventing the header from feeling lopsided.

• Mobile View: Sections are stacked with equal spacing and centred elements, preserving balance in a vertical layout suited for smaller screens.

Examples of Contrast on the LEGO Website:

• Text and Background: White or yellow text is used on dark backgrounds (e.g. banner images), and black or dark text on light backgrounds, making content easy to read.

• Call-to-Action Buttons: Buttons like “Add to Bag” or “Shop Now” are in bright colours (e.g. blue, yellow, or red) that stand out against the surrounding content.

• Product Thumbnails: Bold colours of LEGO sets contrast strongly with neutral backgrounds, making the products pop and attract attention.

• Sale and Promotion Labels: Discounts or special offers use red or yellow tags that contrast with the usual site colours, drawing the user’s eye immediately.

• Hover Effects: Interactive elements such as buttons or product cards use contrast changes (e.g. background darkens or border appears) to show they are clickable.

Examples of Harmony on the LEGO Website:

• Consistent Colour Palette: The site uses LEGO’s signature colours (red, yellow, blue, black, white) throughout, creating a unified and familiar brand experience.

• Typography: Fonts are used consistently across headings, body text, and buttons, which helps maintain a harmonious and professional appearance.

• Icon and Button Styles: Icons (e.g. cart, user profile, search) and buttons share consistent shapes, outlines, and animations, contributing to a cohesive interface.

• Spacing and Layout: Margins, padding, and alignment are consistent across all pages, making each section feel like part of a unified design.

• Product Presentation: Product images follow the same framing, lighting, and background style, creating visual harmony across listings and pages.

Examples of Repetition on the LEGO Website:

• Navigation Structure: The top menu bar with categories like “Shop,” “Discover,” and “Help” is repeated on every page, helping users know where to find information.

• Product Cards: Each product uses a repeated format: image, name, price, and “Add to Bag” button. This consistent structure makes browsing easier.

• Icons and Buttons: Icons (cart, user, search) and buttons use repeated shapes, sizes, and colours throughout the site for visual consistency.

• Section Layouts: Sections such as “Recommended for You,” “Popular Sets,” and “New Releases” follow a repeated horizontal scrolling format.

• Colour and Branding: LEGO’s red and yellow brand colours are repeated throughout the site in banners, buttons, and labels, reinforcing brand identity.

Examples of Hierarchy on the LEGO Website:

• Homepage Banners: Large images with bold headlines and smaller subtext create a clear visual order, drawing attention to key promotions first.

• Product Pages: Product names appear in large, bold text, followed by price, reviews, and then detailed descriptions, guiding the user from most important to least.

• Call-to-Action Buttons: Buttons like “Add to Bag” or “Shop Now” are larger, brightly coloured, and centrally placed, making them stand out as the next step.

• Navigation Menu: Primary categories (e.g. “Shop,” “Discover”) are placed at the top, while subcategories appear only after interaction, showing importance levels.

• Text Styling: Fonts vary in size and weight — headings are bold and larger, while supporting details are smaller — helping users quickly scan for key info.

Examples of Proximity on the LEGO Website:

• Product Listings: Product image, name, price, and “Add to Bag” button are grouped closely together, showing they belong to the same item.

• Navigation Menu: Related links such as “Shop by Age,” “Shop by Theme,” and “Offers” are grouped in dropdown menus, helping users find related content easily.

• Checkout Section: Shipping details, payment options, and order summary are placed near each other, showing they are part of the same process.

• Homepage Sections: Headings are positioned close to their related images and descriptions, clearly linking the content together.

• Footer Links: Information like “Customer Service,” “About Us,” and “Legal” are grouped under clear headings, showing their related purpose.

Examples of Colour Use on the LEGO Website:

• Brand Identity: LEGO’s primary colours (red, yellow, blue) are used consistently across the site to reinforce brand recognition and create harmony.

• Contrast: Bright colours (e.g. yellow buttons on dark backgrounds) are used to create contrast, making important elements like calls-to-action stand out.

• Hierarchy: Colour intensity and brightness are used to highlight what’s most important. For example, “Add to Bag” buttons are brighter than surrounding text, drawing attention first.

• Repetition: Consistent use of colour for buttons, icons, and headings helps users quickly recognise similar functions or sections across the site.

• Grouping (Proximity and Colour): Background shades (e.g. white, grey, or coloured panels) are used to visually separate sections, aiding in grouping related content.

Examples of Form Use on the LEGO Website:

• Product Thumbnails: LEGO sets are shown in 3D-rendered images or angled photos that emphasise their physical form, helping users visualise the product.

• Buttons and Icons: Rounded rectangles and consistent button shapes provide a familiar and clickable form, supporting usability and harmony.

• Homepage Visuals: Large banners feature LEGO models with clear form and structure, using shadows and depth to create visual interest and contrast.

• Category Icons: Icons representing age ranges, themes, or collections use simplified forms that are easy to recognise and differentiate.

• Interactive Elements: Hover effects on buttons and cards create a sense of movement and depth, reinforcing form through visual feedback.

Examples of Line Use on the LEGO Website:

• Dividers Between Sections: Thin horizontal lines are used to separate content areas, helping to create clear structure and visual hierarchy.

• Navigation Menus: Lines and borders are used to group dropdown items, improving proximity and making relationships between links clearer.

• Product Cards: Subtle lines around product tiles or within cards separate image, title, price, and button, guiding the eye through the layout.

• Grid Layouts: Invisible or faint lines structure the grid of products, creating alignment and balance across the page.

• Hover Effects and Underlines: Interactive text links often use underlines or bottom borders on hover, using line to signal interactivity.

Examples of Proportion Use on the LEGO Website:

• Product Cards: Images are larger than text and buttons, reflecting their importance and drawing users’ attention first.

• Headings vs Body Text: Headings are significantly larger than supporting text, establishing hierarchy and helping users scan pages easily.

• Call-to-Action Buttons: Buttons like “Add to Bag” or “Shop Now” are proportionally larger than nearby text to make them visually dominant and easily clickable.

• Hero Banners: Featured sections on the homepage use oversized images and bold text to emphasise new or promoted products.

• Icons and UI Elements: Icons are proportionally balanced with the text and buttons they relate to, maintaining visual harmony and clarity.

Examples of Scale Use on the LEGO Website

• Hero Banners: Large-scale images and headlines at the top of the homepage draw immediate attention to featured products or promotions.

• Product Images: Product images are scaled larger than text or price to highlight the product and help users view details clearly.

• Call-to-Action Buttons: Buttons like “Add to Bag” are scaled up compared to surrounding text, making them easy to notice and interact with.

• Heading Sizes: Main headings are larger than subheadings and body text, creating a clear hierarchy and improving readability.

• Mobile Responsiveness: On smaller screens, elements are rescaled to maintain usability and visual balance while keeping the most important items easy to tap.

Examples of Shape Use on the LEGO Website:

• Buttons and Input Fields: Rectangular buttons with slightly rounded corners are used consistently, creating a clear and approachable interface.

• Icons: Simple geometric shapes (circles, squares, and rectangles) are used for icons like search, cart, and profile, supporting clarity and consistency.

• Product Images: LEGO sets are often photographed in ways that highlight their blocky, angular shapes, reinforcing the brand’s visual identity and creating harmony.

• Content Blocks: Sections of content are arranged in rectangular containers, helping users recognise grouped information and maintaining alignment.

• Promotional Badges: Shapes like stars or rounded tags are used to highlight promotions or featured products, creating visual contrast and drawing attention.

Examples of Space Use on the LEGO Website:

• Whitespace Around Elements: Generous spacing between images, text, and buttons helps reduce clutter, making the content easier to read and improving overall clarity.

• Product Grids: Consistent spacing between product cards ensures balance and alignment, making it easy to scan and compare items.

• Section Separation: Clear space between homepage sections (e.g. banners, featured sets, and categories) defines each area and guides the user’s flow down the page.

• Navigation and Dropdowns: Menu items are spaced out to prevent accidental clicks and improve accessibility, especially on mobile devices.

• Text Blocks: Paragraphs and headings are spaced with clear margins and line spacing, enhancing readability and visual hierarchy.

Examples of Tone Use on the LEGO Website:

• Backgrounds and Overlays: Soft greys and muted tones are used behind text and product sections to maintain contrast while ensuring readability and a clean, modern look.

• Product Photography: Lighting and colour tone in product images are consistent, using bright and vibrant tones that reflect LEGO’s playful and energetic brand.

• Typography Tone: Bold, cheerful colours like red, yellow, and white are used in headlines and calls to action, reinforcing a friendly and enthusiastic tone.

• Hover Effects: Subtle tonal shifts when hovering over buttons or links signal interactivity while maintaining a consistent visual style.

• Seasonal and Promotional Themes: Darker or lighter tones may be used in themed promotions (e.g. Halloween, Christmas) to reflect mood while staying within the LEGO aesthetic.

Examples of Texture Use on the LEGO Website:

• Product Images: High-resolution photos show the surface detail of LEGO bricks — their gloss, studs, and seams — giving a sense of physical texture and realism.

• Background Graphics: Some banners and themed sections use illustrated or photographic textures (e.g. bricks, walls, packaging) to add depth and visual interest.

• Hover Effects: Subtle shadowing or lighting changes on hover create the illusion of tactile response, enhancing interactivity through implied texture.

• Thematic Pages: Pages for specific sets or franchises (e.g. Star Wars, Technic) may include gritty, smooth, or metallic textures in the background to match the theme’s tone.

• Contrast and Depth: Textured visuals are used sparingly to contrast with flat design elements, helping key content stand out without overwhelming the user.

Activity 1: Fitness Tracker

Positive Impacts:

• Improved awareness of health metrics (steps, heart rate, sleep)

• Motivation to achieve daily activity goals

Negative Impacts:

• Increased stress and anxiety from unmet goals

• Obsessive behaviour affecting mental health

• Disrupted work-life balance due to constant checking

Refinements:

• Introduce “rest days” or flexible goals

• Provide positive feedback without pressure

• Add mental health check-ins or screen-time warnings

Activity 2: Study App

Positive Impacts:

• Helps Jamie stay organised with study tasks

• Improves digital literacy through regular use

Negative Impacts:

• Privacy risk from data collection

• Financial pressure to upgrade to premium

• Distracting ads reduce usability

Refinements:

• Limit ad tracking and data collection

• Offer ad-free version for education users

• Improve transparency in privacy policy

Activity 3: VR Social Platform

Positive Impacts:

• Enhances social interaction in a safe space

• May reduce social anxiety for some users

Negative Impacts:

• Avoidance of real-life interactions

• Excessive screen time leading to fatigue

• Risk of emotional over-reliance on digital spaces

Refinements:

• Add usage time limits or reminders to log off

• Encourage real-life meetups or offline goals

• Include features to track emotional well-being

Activity 1: Facial Recognition in Public Spaces

Equity & Inclusion:

• Studies show facial recognition is significantly less accurate for people with darker skin tones, women, and young people. This can lead to disproportionate targeting, mistaken identity, and harassment, particularly affecting minority and vulnerable groups.

• People from culturally and linguistically diverse (CALD) backgrounds may be overrepresented in databases used for surveillance, reinforcing systemic bias.

Well-being & Safety:

• Although promoted as a safety tool, the system may create anxiety and discomfort. Citizens may feel they are constantly monitored, even when not doing anything wrong.

• It can erode public trust in government institutions and law enforcement, especially among communities with a history of being unfairly policed.

Unintended Societal Effects:

• Normalisation of surveillance may discourage protest and free expression.

• Increased social division as people perceive they are being unfairly watched, especially if surveillance is heavier in lower-income or high-diversity areas.

• Sets a precedent for expanding surveillance technologies without strong public oversight.

Recommendations:

• Implement strict policies defining when and where facial recognition can be used.

• Require transparency about how data is stored, who has access, and for how long.

• Mandate third-party bias audits and ban use in schools or areas not proven to benefit from it.

• Provide clear opt-out mechanisms or alternatives for those who do not consent to be scanned.

Activity 2: AI Hiring Tool

Economic Participation:

• Automating hiring processes can save time and reduce some biases, but often also reduces job opportunities for people with non-traditional experience or resumes (e.g. career changers, refugees, older adults).

• If the AI prefers characteristics based on previous successful hires (e.g. attending elite schools), it reinforces existing barriers to economic mobility.

Equity & Inclusion:

• Marginalised groups (e.g. women, First Nations people, people with disabilities) may be excluded due to algorithmic bias in resume screening.

• AI trained on biased historical hiring data may unintentionally penalise applicants based on name, gender, or cultural background.

• Neurodivergent applicants or those with non-linear career paths may be filtered out unfairly.

Social Justice:

• AI hiring lacks transparency; candidates don’t know how decisions are made, and there may be no way to appeal or request human review.

• Raises legal and ethical concerns under anti-discrimination laws, especially if fairness was not considered in the AI’s design.

Recommendations:

• Require human review at critical stages to catch unfair rejections.

• Use diverse training data and conduct regular audits to identify discriminatory outcomes.

• Clearly inform applicants how AI is used and provide meaningful opt-out or appeal options.

• Engage legal and ethical experts when designing or purchasing AI systems.

Activity 3: School Communication App

Community & Culture:

• The app strengthens parent–teacher communication for tech-savvy families, increasing engagement and transparency.

• However, it weakens relationships with families who lack devices, don’t speak English well, or feel intimidated by digital tools. These families may feel excluded from the school community.

Equity & Inclusion:

• Digital divide is a major issue: low-income households may not have smartphones or internet. Remote or Indigenous communities may have limited connectivity.

• Migrant parents or carers with low literacy may struggle with apps in English.

• Children in these homes miss updates, permission notes, and homework alerts, increasing inequality.

Education Access and Fairness:

• Homework reminders, timetable updates, or absence notifications may never reach some families, leading to lower attendance, missed assignments, and disengagement.

• Some students may be embarrassed that their families don’t use the app, affecting confidence and sense of belonging.

Recommendations:

• Provide printed newsletters and SMS updates for families without app access.

• Translate communications into relevant community languages.

• Survey families to identify barriers to access and target support.

• Offer school workshops on digital literacy for parents.

• Design the app to function on low-bandwidth connections and older devices.

Activity 1: Digital Tax Filing System

Economic Productivity:

• Businesses save time on paperwork and manual calculations, reducing admin overhead.

• The Australian Taxation Office also reduces manual processing, increasing speed and accuracy of returns.

• Integration with accounting software means less duplication and fewer errors across the system.

Public Revenue & Policy:

• Improved compliance through automated prompts and reduced opportunities for errors or fraud.

• Broader tax base coverage due to ease of use for freelancers and small businesses.

• Potential need to update tax regulations to align with digital record-keeping and enforcement.

Cost-Benefit & ROI:

• Initial development costs may be high, but savings in processing and increased revenue offset these over time.

• Reduced costs for physical infrastructure (e.g. fewer tax offices and mailing systems).

• High return on investment if adoption is widespread.

Employment & Workforce:

• Less need for front-counter staff and manual data entry roles.

• New roles created in software development, cybersecurity, and digital customer support.

• Upskilling programs required for current tax office staff.

Activity 2: E-Commerce Platform for Rural SMEs

Market Growth & Trade:

• Enables rural producers to reach urban and international customers directly, bypassing middlemen.

• Increases potential for exports of artisan goods, local produce, and niche products.

• Stimulates competition and innovation among regional businesses.

Inclusion & Access:

• Reduces geographic disadvantage by levelling the playing field for remote communities.

• Supports Indigenous-owned or women-led rural enterprises to access new markets.

• Requires support for internet access and digital literacy to be truly inclusive.

Employment & Workforce:

• New jobs in order fulfilment, digital marketing, product design, and customer service.

• Rural youth may see more reason to remain in their communities with online income opportunities.

• Requires training programs to build e-commerce and logistics skills.

Resilience & Innovation:

• Builds economic resilience by diversifying rural income sources.

• Encourages innovation through digital entrepreneurship.

• Helps communities adapt to agricultural downturns or climate-related challenges by tapping into non-farming revenue.

Activity 3: AI Automation in Manufacturing

Economic Productivity:

• AI systems increase output speed and reduce waste through precise quality control.

• Operational costs decrease due to fewer errors and downtime.

• Global competitiveness improves, attracting foreign investment and increasing exports.

Employment & Workforce:

• Low-skilled jobs (e.g. manual inspection, warehouse roles) are displaced.

• High demand for data analysts, AI engineers, and robotics technicians.

• Requires strong national focus on reskilling and vocational education reform to prevent unemployment.

Resilience & Innovation:

• Automated systems adapt quickly to changes in demand or disruptions in supply chains.

• AI encourages innovation in product design and customisation.

• Stronger ability to compete with advanced economies in the global tech-driven market.

Public Revenue & Policy:

• Decline in payroll tax from lost jobs may impact revenue.

• Potential for new tax policies targeting automation or AI-driven productivity.

• Public investment needed in training subsidies, social safety nets, and digital infrastructure.

Activity 1: Sorting Student Names

1. Take a list of all student names

2. Compare the first two names

3. If they are out of order, swap them

4. Repeat the comparison for the next pair

5. Continue until the entire list is sorted

6. Repeat the process if needed until no more swaps are made

Activity 2: Vending Machine Simulation

1. Display available items and their prices

2. Wait for the user to select an item

3. Ask the user to insert money

4. Check if the inserted amount is equal to or greater than the item price

5. If not enough, ask for more money

6. If enough, dispense the item

7. Give change if needed

Activity 3: Password Strength Checker

1. Get the password input from the user

2. Check if the password is at least a minimum number of characters (e.g. 8)

3. Check if it contains at least one uppercase letter

4. Check if it contains at least one number

5. Check if it contains at least one special character (e.g. !, @, #)

6. If all rules are met, mark as “Strong”; otherwise, mark as “Weak”

1. Data-driven solutions collect or access quality data, query that data, and interpret it to provide insight.

2. The DIKW Pyramid represents how raw data is transformed into wisdom through context, experience, and action.

3. Information is data with added context such as who, what, when, and where.

4. Applying action to knowledge transforms it into wisdom.

5. Value increases up the DIKW Pyramid because each level adds more meaning and usefulness.

6. 3000mm becomes wisdom when you realise it won’t fit in your car and decide to get it delivered.

7. Data-driven programming involves filtering, transforming, and aggregating structured data.

8. The three layers are external (UI), logical (data organisation), and internal (storage systems).

9. The external layer shows the user interface and represents data in a meaningful way.

10. The logical layer ensures data integrity, reliability, and validity.

1. The two key factors are the timeliness of data acquisition and the ownership of the data.

2. Personal ownership relates to individual data, corporate ownership to organisational data, and public ownership to government or shared public data.

3. Data integrity means keeping data accurate, complete, consistent, and protected from unauthorized changes or damage.

4. Data must be complete, accurate, up to date, consistent, secure, and relevant.

5. A data anomaly is an error or inconsistency that can affect accuracy, completeness, or consistency in a database.

6. Insertion anomalies prevent adding data without unnecessary information, deletion anomalies cause loss of important data, and update anomalies create inconsistencies during changes.

7. Proper design, normalization, and data validation reduce anomalies and improve data reliability.

8. Threats include malware (viruses, worms, Trojans, ransomware, spyware, adware, rootkits), data theft, identity theft, and invasion of privacy.

9. User-level access control limits user access based on roles, enforces policies, and allows monitoring of activities to prevent unauthorized use.

10. Encryption is a reversible process using a key to scramble and unscramble data, while hashing is a one-way process that cannot be reversed, used for secure password storage.

1. Representation refers to how different types of data, like text and numbers, are converted into a format (usually 0s and 1s) that computers can understand.

2. ASCII represents each letter, number, or symbol as a specific number, like ‘A’ being 65.

3. Unicode is preferred because it can represent characters from almost all languages, as well as emojis and special symbols.

4. Unicode can represent non-English characters, emojis, and symbols from global languages that ASCII cannot.

5. Knowing whether your data uses ASCII or Unicode ensures it is interpreted and displayed correctly.

6. Consistent data formats ensure accuracy and reliability when storing and using data in a database.

7. 100,000 can also be represented as $10^5$; both are the same value but different formats.

8. A data format must be decided early to ensure consistency across all records in a database.

9. The international standard for dates is yyyy-mm-dd, known as ISO 8601.

10. In the 24-hour system, 1:15pm is written as 13:15; in the 12-hour system, it’s written as 1:15pm.

11. Time formatting uses H/h for hours, m for minutes, s for seconds, and A for AM/PM.

12. 0 represents a required digit, while 9 represents an optional digit between 0 and 9.

13. A common mobile number format is 0000 000 000.

14. Currency often uses two decimal places, such as $90.00.

1. A flat file database stores data in a simple table with rows and columns, where each row is a record and each column is a field.

2. Flat file databases can’t handle complex relationships because they only use a single table with no links between data.

3. Flat file databases use one table without relationships, while relational databases use multiple linked tables with predefined relationships.

4. Data in a relational database is organized into tables with rows representing records and columns representing attributes.

5. A primary key is a unique column in a table that identifies each row.

6. A foreign key is a primary key from one table used in another table to create a relationship between them.

7. SQL is used to add, update, delete, and retrieve data in relational databases.

8. ACID stands for Atomicity, Consistency, Isolation, and Durability.

9. Atomicity ensures that all steps in a transaction are completed or none are, preventing partial changes.

10. Consistency ensures that a transaction moves the database from one valid state to another, following the rules of the schema.

11. Isolation prevents interference between concurrent transactions so each behaves as if it’s the only one running.

12. Durability makes sure committed changes are permanent and survive system crashes.

13. A data value is the actual piece of information in a cell of a table.

14. Relational databases are good for business and web apps because they handle structured data and complex relationships efficiently.

1. The main goal of database normalisation is to minimise data redundancy and eliminate anomalies by organising data into smaller, related tables.

2. Data redundancy is the unnecessary repetition of data, which increases database size and risks data integrity.

3. An insertion anomaly happens when adding new data requires repeating existing data, leading to inefficiency and potential errors.

4. A deletion anomaly occurs when removing one dataset unintentionally deletes related information that should have been kept.

5. Update anomalies cause inconsistencies when a change isn’t applied everywhere, resulting in conflicting data about the same entity.

6. Normalisation reduces redundancy by breaking large tables into smaller ones and linking them through common fields.

7. The “Divide and Rule” approach means splitting a large table into multiple smaller tables, each focused on one concept.

8. The STUDENTS TABLE is split into a Student Table (rollno, name, branch) and a Branch Table (branch, hod, office_tel).

9. Normalisation solves the insertion anomaly by allowing new student entries without repeating branch details, which are stored separately.

10. After normalisation, updating the HOD requires a change in only one place—the Branch Table—ensuring consistency for all students.

Table 1

Table 2

Table 3

Table 4

Table 1

Enrolments Table

Courses Table

Table 2

Transactions Table

Products Table

Table 3

Borrowings Table

Books Table

Table 4

Attendance Table

Sessions Table

Table 1

Employee Table

Department Table

Table 2

Book Table

Publisher Table

Table 3

Customer Table

Suburb Table

Table 4

Product Table

Student Table

Subject Table

Department Table

Enrolment Table

1. Collection and sale of personal data, should address:

• Lack of informed consent

• Limited user understanding of terms and conditions

• Transparency issues with companies

• Ethical concerns of data being used or sold without clear permission

2. Risks from poor data storage and security should address:

• Data breaches as targets for hackers

• Identity theft

• Financial loss

• Reputational damage and emotional distress

3. Responsible data handling practices should address:

• Transparency about data use and sharing

• Clear communication with users

• Building trust through honesty

• User confidence and stronger relationships

1. How is information similar to and different from traditional physical commodities like oil or gold?

   • Similarities: has economic value, can be traded, drives industries

   • Differences: intangible, can be copied/shared infinitely, low marginal cost

2. What characteristics make data valuable as an economic resource in the digital age?

   • Intangibility

   • Tradability (databases, reports, software, media)

   • Value creation (informs decisions, competitive advantage)

   • Market dynamics (supply, demand, private/public goods)

   • Low marginal cost of reproduction

3. What ethical and legal concerns can arise from treating personal data as a tradable commodity?

   • Exploitation of individuals’ digital footprints

   • Lack of informed consent in data collection

   • Privacy violations and surveillance

   • Risk of data misuse by third parties

   • Regulatory and legal compliance issues

1. Privacy Violations – How can collecting data without proper consent infringe on privacy?

   • Collecting without authorization or consent exposes sensitive information

   • Breaches confidentiality

   • Even anonymized data can sometimes be re-identified, leading to privacy breaches

2. Informed Consent – What makes informed consent critical for ethical data collection?

   • Individuals must clearly understand what is being collected

   • They need to know how the data will be used

   • They should be told with whom the data may be shared

   • Many consent processes are inadequate because terms are too complex or unclear

3. Data Security – Why is data security an ethical obligation for organizations?

   • Prevents unauthorized access to data

   • Reduces risks of breaches or leaks

   • Protects individuals from identity theft

   • Prevents financial harm

   • Reduces reputational damage to individuals and organizations

   • High-profile breaches highlight the importance of robust security

4. Bias and Discrimination – How can poor data handling reinforce bias?

   • Datasets can be unrepresentative

   • Algorithms may perpetuate or amplify bias if not carefully managed

   • Leads to unfair or discriminatory outcomes

   • Facial recognition has been criticised for racial bias and inaccuracies

5. Transparency and Accountability – Why are both needed in ethical data collection?

   • Organizations must clearly state what data is collected

   • Must explain why it is collected

   • Must explain how it will be used

   • Transparency enables informed choices by individuals

   • Lack of transparency erodes trust and can lead to misuse or abuse

6. Manipulative and Exploitative Practices – How can data be misused unethically?

   • Used for manipulative marketing

   • Enables psychological profiling

   • Can drive social manipulation

   • Undermines individual autonomy

   • Can threaten democratic processes

7. Data Ownership and Control – What are the debates about who owns personal data?

   • Ongoing debate over whether individuals or organizations own data

   • Issues of who has the right to control its use

   • Increasingly important as data becomes a valuable asset

8. Data Minimization and Purpose Limitation – Why should organizations limit what data they collect?

   • Only collect data necessary for a specific purpose

   • Do not retain data longer than needed

   • Helps balance commercial interests with protecting individual rights

9. Fairness in Use and Retention – Why is using data beyond original intent unethical?

   • Using data for other purposes breaches fairness principles

   • Lack of explicit consent for new uses is unethical

   • Even if thought beneficial, it erodes user trust

10. Legal and Regulatory Compliance – How do global laws influence ethical handling of personal data?

    • GDPR (EU): explicit consent, minimization, rights to access/delete, data portability, breach notification, heavy penalties

    • US: mix of federal sectoral laws (HIPAA, GLBA, COPPA, FERPA, FCRA) and state laws (CCPA, CDPA, Colorado Privacy Act)

    • China: PIPL with strict consent, minimization, cross-border restrictions, severe penalties

    • Australia: Privacy Act & APPs requiring transparency, data quality/security, access/correction rights, cross-border limits

    • International influence: GDPR drives cookie consent popups, COPPA shapes age restrictions on social media

1. Why do the Australian Privacy Principles exist, and what overall purpose do they serve?

   • Govern how organizations and government agencies handle personal information

   • Ensure privacy, transparency, and accountability

   • Protect individual rights in collection, use, storage, and disclosure

2. How do the APPs balance individual rights with the needs of organizations and government agencies?

   • Give individuals rights to access, correction, and privacy

   • Allow organizations to collect and use data where necessary for functions

   • Impose safeguards such as consent, limitation, and accountability

3. What might happen to public trust if organizations consistently fail to follow the APPs?

   • Erosion of user confidence

   • Increased concern about privacy and misuse of information

   • Potential withdrawal from services or complaints to regulators

4. How do the APPs connect with global privacy frameworks, such as the GDPR?

   • Share common principles: consent, minimization, access, correction, security

   • Influence of GDPR on international data protection practices

   • Help Australian organizations align with global standards

5. Why is it important for organizations to maintain a clear and up-to-date privacy policy?

   • Open and transparent management of personal information

   • Requirement for clearly expressed and current privacy policy

6. In what situations might an individual reasonably choose to deal with an organization anonymously or under a pseudonym?

   • APP requires option of anonymity or pseudonymity

   • Exceptions: impracticable or unlawful to do so

7. What limits are placed on organizations when collecting personal information?

   • Collect only information necessary for functions

   • Must be collected by lawful and fair means

8. How should an organization handle personal information it receives that it did not ask for?

   • Assess whether it could have been collected under APP 3

   • If not, must destroy or de-identify it

9. What information must an organization provide to an individual when collecting their personal information?

   • Notify individual at time of collection

   • Purpose of collection

   • Any third parties with whom data may be shared

10. Under what conditions can an organization use or disclose personal information for purposes other than the original collection?

• Use or disclose only for the collected purpose

• Exceptions apply in specific lawful cases

11. What obligations do organizations have if they use personal information for direct marketing?

• Only use under certain conditions

• Must provide simple opt-out option

12. What steps must organizations take before sending personal information overseas?

• Take reasonable steps to ensure overseas recipients comply with APPs

13. Why are organizations restricted in their use of government-related identifiers such as Medicare numbers?

• Cannot adopt, use, or disclose government identifiers

• Limited exceptions where permitted by law

14. What steps must organizations take to ensure the personal information they collect is accurate and complete?

    • Take reasonable steps to ensure accuracy

    • Ensure information is up-to-date

    • Ensure information is complete

15. What kinds of measures should organizations implement to protect personal information?

    • Protect against misuse and interference

    • Prevent loss of information

    • Guard against unauthorized access, modification, or disclosure

16. What rights do individuals have to access their personal information, and what are the exceptions?

• Right to access personal information held by organization

• Subject to lawful exceptions

17. How should organizations handle requests to correct inaccurate or misleading personal information?

• Take reasonable steps to correct information

• Ensure it is accurate, up-to-date, complete, relevant, not misleading

1. What is open data, and how is it typically made available?

   • Freely available for anyone to access, use, modify, and share

   • Published by governments, public institutions, or private organizations

   • Provided in accessible, machine-readable formats

2. What are the key features that make data truly “open”?

   • Freely accessible to all, regardless of user or purpose

   • Usable, reusable, and redistributable without restrictions

   • Structured for easy analysis and integration with other datasets

3. How does open data promote transparency and accountability in governments and organizations?

   • Enables citizens to scrutinize actions and performance

   • Increases transparency and allows public oversight

   • Example: showing school performance or government spending to empower communities

4. In what ways can open data drive innovation and contribute to economic growth?

   • Stimulates creation of new products, services, and business models

   • Fosters entrepreneurship and job creation

   • Example: release of weather and GPS data created new industries and billions in value

5. How does open data improve public services and government efficiency?

   • Sharing data across agencies improves decision-making

   • Reduces duplication of effort

   • Identifies unnecessary spending

   • Improves overall service delivery

6. Why is open data important for scientific research and collaboration?

   • Accelerates discovery by enabling validation of findings

   • Allows researchers to build upon existing work

   • Encourages collaboration across disciplines and borders

7. How can open data empower individuals and communities to make informed decisions?

   • Provides access to relevant information

   • Enables informed choices

   • Supports participation in civic life

   • Helps advocate for community needs

8. What role does open data play in encouraging social welfare and civic participation?

   • Informs public debate

   • Supports evidence-based policy

   • Enables social innovation

   • Improves social outcomes

9. What are some major open data sources available in Australia at national, state, and local government levels?

   • National: Data.gov.au, ABS, NationalMap

   • State/Territory: Data.NSW, Data.VIC, Data.Qld, DataSA, DataWA, LIST (Tasmania), DataACT, NT Open Data Portal

   • Council: Brisbane, Gold Coast, Logan, Redland open data portals

10. What is de-identification, and why is it important when publishing open data?

    • Removing or altering personal information so individuals cannot be identified

    • Protects privacy while allowing analysis and research

    • Helps organizations comply with laws like APPs or GDPR

    • Enables freer data sharing for research, policy, and innovation

11. What are the key steps involved in de-identifying data before it is released?

    • Removing direct identifiers (names, addresses, phone numbers, emails, Medicare numbers)

    • Modifying or generalizing indirect identifiers (e.g., age ranges instead of birth dates, partial removal of postcodes)

    • Applying data masking or perturbation (e.g., swapping data, adding noise, aggregating)

12. How does de-identification help organizations comply with privacy laws such as the APPs or GDPR?

    • Reduces the risk that individuals can be identified

    • Meets requirements of privacy laws regarding personal data handling

    • Allows safe sharing of data for research, policy-making, and innovation

13. What are the limitations and risks associated with de-identification of open data?

    • Not foolproof—re-identification still possible

    • Advances in analytics and other datasets can expose identities

    • Greater risk when datasets are rich or unique

14. Why must de-identification be treated as a continuous process rather than a one-time action?

    • New technologies create new re-identification risks

    • Additional datasets may combine to reveal identities

    • Requires regular review and updating to stay effective

Question 1

Latency is the delay when data travels from source to destination. It is important for gaming because high latency makes actions respond slowly, creating lag and reducing gameplay quality.

Question 2

• Propagation: delay caused by the time signals take to travel through cables or fibre.

• Queuing: delay caused when packets wait in line at routers or switches before being sent.

Question 3

Jitter is the variation in packet arrival times. In video streaming it can cause:

• Stuttering or freezing: video pauses briefly, then suddenly resumes.

• Uneven playback speed: video may speed up or slow down, making motion appear unnatural.

• Frame drops: some frames never display, leading to jerky or jumpy playback.

• Audio-video desynchronisation: sound may lag behind or run ahead of the video.

• Pixelation or visual artifacts: inconsistent delivery can cause blocks or distortions in the image.

• Buffering delays: the video stops to load more data, interrupting smooth viewing.

Question 4

One of:

• Network congestion, where too many packets compete for bandwidth, increases jitter.

• Different routing paths: packets may take different routes across the network, arriving at different times.

• Processing delays: routers and switches may take longer to inspect and forward some packets than others.

• Wireless interference: signals can be disrupted by obstacles or competing devices, causing irregular delivery times.

• Insufficient bandwidth: when too many users or applications compete for the same bandwidth, packet delivery becomes inconsistent.

• Buffering in devices: network devices sometimes hold packets briefly in buffers, releasing them unevenly.

Question 5

QoS guarantee is assurance that certain traffic (e.g. voice or video) will receive priority and required performance, with low latency and minimal packet loss.

Question 6

QoS prioritises voice packets so they are not delayed or dropped, ensuring clear, uninterrupted calls.

Question 7

Timeliness of delivery means data arrives within a timeframe that keeps it relevant and useful, such as real-time updates.

Question 8

Possible answers:

• Video conferencing: delays cause people to talk over each other, breaking the flow of conversation.

• Online gaming: if actions (like moving or shooting) arrive late, players lose accuracy and fairness.

• Stock trading systems: late delivery of market data can cause financial loss if trades are made on outdated prices.

• Emergency services communication: delayed data (like location tracking or medical telemetry) can risk lives.

• Autonomous vehicles: late sensor data could cause unsafe driving decisions.

• Live sports streaming: late delivery results in lag behind the actual event, ruining the real-time experience.

Question 1

Transmission Control Protocol / Internet Protocol; it is the standard suite of rules that allows computers to communicate over the internet.

Question 2

Question 3

Question 4

IP handles addressing and routing so data packets can move between devices on different networks.

Question 5

IPv4 uses 32-bit addresses written as four dotted numbers (e.g., 192.168.1.1), while IPv6 uses 128-bit hexadecimal addresses (e.g., 2001:db8::1) to allow many more unique addresses.

Question 6

IP only delivers packets on a best-effort basis, so TCP adds reliability by resending lost packets and reordering them.

Question 7

One of:

Question 8

One of:

Question 9

It indicates that the site is using HTTPS with a valid security certificate.

Question 10

To transfer files between a client and a server over a network.

Question 11

FTPS encrypts login credentials and file transfers using SSL/TLS, preventing interception.

Question 12

It creates a secure, private tunnel for internet traffic, protecting data from eavesdropping.

Question 13

IKEv2/IPsec; it is fast, secure, and handles switching between Wi-Fi and mobile data smoothly.

Question 14

Live streaming delivers content in real-time, while on-demand lets users watch pre-recorded content at any time.

Question 15

WebRTC, because it provides real-time, low-latency communication directly in browsers.

Question 16

Unicast is one-to-one, broadcast is one-to-all, multicast is one-to-many (a specific group).

Question 17

DHCP.

Question 18

To map an IP address to a device’s MAC address by broadcasting a request on the local network.

Question 1

REST stands for Representational State Transfer. It is an architectural style for designing networked applications that use HTTP to perform CRUD operations on resources.

Question 2

Stateless means the server does not keep track of client sessions. Each request must contain all the information the server needs to process it.

Question 3

Create uses POST, and Delete uses DELETE.

Question 4 JSON is used to exchange data between clients and servers in web applications, often through APIs.

Question 5

One of:

Question 6

Arrays are enclosed in square brackets [ ] and contain a list of values. Example: "students": ["Alice", "Bob", "Charlie"].

Question 7

Data is organised in a hierarchical, tree-like structure using nested tags.

Q8. Give one advantage and one disadvantage of XML compared to JSON.

One of:

Question 9

XML is used for RSS feeds to distribute website updates.

Question 10

CSV uses commas to separate values, while TSV uses tabs.

Question 11

They store data as plain text and have smaller file sizes, making them efficient for storage and transfer.

Question 12

One of:

1. Simple selection (Pass/Fail)

• Error: boundary error (uses > instead of >=, so 50 fails)

BEGIN check_pass
    INPUT mark
    IF mark >= 50 THEN
        OUTPUT "Pass"
    ELSE
        OUTPUT "Fail"
    ENDIF
END

2. Counted loop + accumulator (sum 5 numbers)

• Error: accumulator not initialised (total starts undefined)

BEGIN sum_five_numbers
    DECLARE count AS INTEGER
    DECLARE total AS INTEGER = 0

    FOR count = 1 TO 5
        INPUT num
        total = total + num
    NEXT count
    ENDFOR

    OUTPUT total
END

3. Pre-test loop (countdown)

• Error: infinite loop (counter moves the wrong way)

BEGIN countdown
    INPUT n
    WHILE n > 0
        OUTPUT n
        n = n - 1
    ENDWHILE
    OUTPUT "Done"
END

4. Login attempts

• Error 1: loop condition impossible (login_attempts < 0 will be false when starting at 3)

• Error 2: attempts go up instead of down

BEGIN user_login
    DECLARE login_attempts AS INTEGER = 3

    WHILE login_attempts > 0
        INPUT user_name
        INPUT user_password

        IF is_valid(user_name, user_password) THEN
            OUTPUT "Login successful"
            login_attempts = 0
        ELSE
            login_attempts = login_attempts - 1
            OUTPUT "Invalid. " + login_attempts + " attempts left."
        ENDIF
    ENDWHILE

    OUTPUT "Try again later"
END

5. Nested selection (grading)

• Error: unreachable branches (the first test mark >= 50 catches 70 and 85 before later checks)

BEGIN grade_score
    INPUT mark

    IF mark >= 85 THEN
        OUTPUT "A"
    ELSE IF mark >= 70 THEN
        OUTPUT "B"
    ELSE IF mark >= 50 THEN
        OUTPUT "C"
    ELSE
        OUTPUT "D"
    ENDIF
END

6. Data validation (age range)

• Error: impossible condition (cannot be < 0 AND > 120 at the same time)

BEGIN validate_age
    INPUT age

    IF age < 0 OR age > 120 THEN
        OUTPUT "Invalid age"
    ELSE
        OUTPUT "Age accepted"
    ENDIF
END

Using the Movies database

SELECT dirname
FROM director
WHERE country = "US"

SELECT dirname
FROM director
WHERE country <> "US"

SELECT memname
FROM members
WHERE owes IS NOT NULL

SELECT movname
FROM movie
WHERE movname LIKE "%the%"

SELECT movname
FROM movie
WHERE movname LIKE "Z%"

Using the Repairs database

SELECT owner
FROM repair
WHERE ready = "Yes"

SELECT owner
FROM repair
WHERE type = "iMac" AND ready = "No"

Using the World database

SELECT CountryName
FROM country
WHERE IndepenYear IS NULL AND Capital IS NOT NULL

SELECT *
FROM country
WHERE CountryName IS NULL 
OR Continent IS NULL 
OR Region IS NULL
OR Area IS NULL
OR IndepenYear IS NULL
OR Population IS NULL
OR LifeExp IS NULL
OR GNP IS NULL
OR Government IS NULL
OR Capital IS NULL

SELECT CountryName
FROM country
WHERE Government LIKE "%Constitutional Monarchy%" 
OR Government LIKE "%Republic%"

Using the Movies database

SELECT COUNT(dirnumb)
FROM director
WHERE country = "Australia"

SELECT COUNT(dirname)
FROM director
WHERE dirname LIKE "%John"

SELECT MAX(length)
FROM movie

SELECT SUM(length)
FROM movie

SELECT AVG(time)
FROM repair

SELECT COUNT(job_numb)
FROM repair
WHERE ready = "Yes"

SELECT COUNT(CoCode)
FROM company
WHERE Risk = "High"

SELECT CoName, MAX(YearHigh - YearLow)
FROM company

SELECT CoName, MIN(CurPrice)
FROM company
WHERE (Risk = "Medium" OR Risk = "Low")
AND Exchange = "NYSE"

SELECT CoName
FROM company
WHERE YearHigh - CurPrice < YearHigh * 0.1

Using the Movies database

SELECT COUNT(dirnumb)
FROM director
WHERE country = "Australia"

SELECT movname
FROM movie
ORDER BY year DESC 
LIMIT 5

SELECT movname, year
FROM movie
ORDER BY year, movname

Using the School Database

SELECT stname
FROM student
ORDER BY stname

SELECT stnumb
FROM results
ORDER BY percent DESC
LIMIT 3

SELECT stname, born
FROM student
ORDER BY gender, born

Using the Movies database

SELECT country, COUNT(dirnumb)
FROM director
GROUP BY country

SELECT memberid, COUNT(movienumber)
FROM movies_onhire
GROUP BY memberid

SELECT year, COUNT(movienumb)
FROM movie
GROUP BY year

Using the School database

SELECT subjnumb, AVG(percent)
FROM results
GROUP BY subjnumb

SELECT grade, gender, COUNT(stnumb)
FROM student
GROUP BY grade, gender

Using the Shares database

SELECT Risk, COUNT(CoCode)
FROM company
GROUP BY Risk

SELECT Risk, CoName, MIN(CurPrice)
FROM company
WHERE Exchange = "NYSE"
GROUP BY Risk

Using the Chinook database

SELECT Country, COUNT(CustomerId)
FROM customers
GROUP BY Country
HAVING COUNT(CustomerId) > 1

SELECT AlbumId
FROM tracks
GROUP BY AlbumId
HAVING SUM(Milliseconds)/1000 > 3600

SELECT BillingCountry, SUM(Total)
FROM invoices
GROUP BY BillingCountry
HAVING SUM(Total) > 100
ORDER BY BillingCountry

Using the Schools database

SELECT percent
FROM results
WHERE stnumb IN (
	SELECT stnumb
	FROM student
	WHERE grade = 7
	)

SELECT subjname
FROM subject
WHERE tname IN (
	SELECT tname
	FROM teacher
	WHERE room = "A2"
	)

SELECT subjname
FROM subject
WHERE subjnumb IN (
	SELECT subjnumb
	FROM results
	WHERE percent > 90
	)

SELECT stname
FROM student
WHERE stnumb IN (
	SELECT stnumb
	FROM results
	WHERE subjnumb IN (
		SELECT subjnumb
		FROM subject
		WHERE subjname = "science"
		)
	)
	

SELECT stname
FROM student
WHERE stnumb IN (
	SELECT stnumb
	FROM results
	WHERE percent > 50
	AND subjnumb IN (
		SELECT subjnumb
		FROM subject
		WHERE subjname = "language"
		)
	)

Repairs database

SELECT owner
FROM repair
WHERE id_numb IN (
	SELECT id_numb
	FROM technicians
	WHERE name = "Carrol"
	)

SELECT name
FROM technicians
WHERE id_numb IN (
	SELECT id_numb
	FROM experience
	WHERE type = "iMac" AND qualification = "N"
	)

SELECT rate
FROM devices
WHERE type IN (
	SELECT type
	FROM repair
	WHERE owner = "Byrne"
	)

SELECT owner
FROM repair
WHERE type IN (
	SELECT type
	FROM devices
	WHERE priority = "H"
	)

SELECT qualification
FROM experience
WHERE (id_numb, type) IN (
  SELECT id_numb, type
  FROM repair
  WHERE owner = "James"
)

Using Repairs database

SELECT repair.job_numb, technicians.name
FROM repair
JOIN technicians ON repair.id_numb = technicians.id_numb

SELECT technicians.name, experience.type
FROM technicians
JOIN experience ON technicians.id_numb = experience.id_numb
WHERE experience.qualification = "E"

SELECT repair.id_numb, technicians.name, repair.type, repair.owner, repair.ready
FROM repair
JOIN technicians ON repair.id_numb = technicians.id_numb
ORDER BY repair.ready DESC

SELECT repair.job_numb, repair.owner, repair.type, repair.time, repair.time * devices.rate AS "Cost"
FROM repair
JOIN devices ON repair.type = devices.type
WHERE repair.ready = "Yes"

Using the Chinook database

SELECT albums.Title AS "Album", artists.Name AS "Artist"
FROM albums
JOIN artists ON albums.ArtistId = artists.ArtistId
ORDER BY artists.Name

SELECT tracks.Name AS "Track"
FROM tracks
JOIN genres ON tracks.GenreId = genres.GenreId
WHERE genres.Name LIKE "%Metal%"

SELECT tracks.Name AS "Track", albums.Title AS "Album", genres.Name AS "Genre", tracks.Composer, tracks.Milliseconds / 1000 AS "Length", tracks.UnitPrice
FROM tracks
JOIN albums ON tracks.AlbumId = albums.AlbumId
JOIN genres ON tracks.GenreId = genres.GenreId
JOIN artists ON albums.ArtistId = artists.ArtistId
WHERE artists.Name = "Def Leppard"

Using the Schools database

SELECT student.stname AS "Student", subject.subjname AS "Subject", results.percent AS "Result"
FROM student
JOIN results ON student.stnumb = results.stnumb
JOIN subject ON results.subjnumb = subject.subjnumb

SELECT subject.subjname AS "Subject", student.gender AS "Gender", COUNT(student.gender) AS "Enroled"
FROM subject
JOIN results ON subject.subjnumb = results.subjnumb
JOIN student ON results.stnumb = student.stnumb
GROUP BY subject.subjname, student.gender

SELECT teacher.tname, AVG(results.percent)
FROM teacher
JOIN subject ON teacher.tname = subject.tname
JOIN results ON subject.subjnumb = results.subjnumb
GROUP BY teacher.tname

Activity 1

-- Product table has no foreign keys

CREATE TABLE "Product" (
	"product_id" INTEGER,
	"name" TEXT NOT NULL,
	"quantity" INTEGER NOT NULL,
	PRIMARY KEY("product_id" AUTOINCREMENT)
);

-- Supplier table has no foreign keys

CREATE TABLE "Supplier" (
	"supplier_id" INTEGER,
	"name" TEXT NOT NULL,
	"email" TEXT NOT NULL,
	PRIMARY KEY("supplier_id" AUTOINCREMENT)
);

-- Component table has no foreign keys

CREATE TABLE "Component" (
	"component_id" INTEGER,
	"name" TEXT NOT NULL,
	"description" TEXT NOT NULL,
	PRIMARY KEY("component_id" AUTOINCREMENT)
);

-- Tables for foreign keys exist

CREATE TABLE "Component Supplier" (
	"component_id" INTEGER,
	"supplier_id" INTEGER,
	PRIMARY KEY("component_id","supplier_id"),
	FOREIGN KEY("component_id") REFERENCES "Component"("component_id"),
	FOREIGN KEY("supplier_id") REFERENCES "Supplier"("supplier_id")
);

-- Tables of foreign keys exist

CREATE TABLE "Product Components" (
	"product_id" INTEGER,
	"component_id" INTEGER,
	"quantity" INTEGER NOT NULL,
	PRIMARY KEY("product_id","component_id"),
	FOREIGN KEY("component_id") REFERENCES "Component"("component_id"),
	FOREIGN KEY("product_id") REFERENCES "Product"("product_id"),
	FOREIGN KEY("quantity") REFERENCES ""
);

Activity 2

-- Students table has no foreign keys

CREATE TABLE "Students" (
	"student_id" INTEGER,
	"name" TEXT NOT NULL,
	"form" TEXT NOT NULL,
	PRIMARY KEY("student_id" AUTOINCREMENT)
);

-- Genre table has no foreign keys

CREATE TABLE "Genre" (
	"genre_id" INTEGER,
	"name" TEXT NOT NULL,
	PRIMARY KEY("genre_id" AUTOINCREMENT)
);

-- Nationality table has no foreign keys

CREATE TABLE "Nationality" (
	"nationality_id" INTEGER,
	"name" TEXT NOT NULL,
	PRIMARY KEY("nationality_id" AUTOINCREMENT)
);

-- Table of foreign key exists

CREATE TABLE "Author" (
	"author_id"	INTEGER,
	"name" TEXT NOT NULL,
	"nationality" INTEGER NOT NULL,
	PRIMARY KEY("author_id" AUTOINCREMENT),
	FOREIGN KEY("nationality") REFERENCES "Nationality"("nationality_id")
);

CREATE TABLE "Book" (
	"book_id" INTEGER,
	"title" TEXT NOT NULL,
	"author" INTEGER NOT NULL,
	"genre" INTEGER NOT NULL,
	"year" INTEGER NOT NULL,
	PRIMARY KEY("book_id" AUTOINCREMENT),
	FOREIGN KEY("author") REFERENCES "Author"("author_id"),
	FOREIGN KEY("genre") REFERENCES "Genre"("genre_id")
);

-- Tables of foreign keys exist

CREATE TABLE "Loan" (
	"book_id"	INTEGER,
	"student_id"	INTEGER,
	"borrow_date"	TEXT NOT NULL,
	"return_date"	TEXT,
	PRIMARY KEY("book_id","student_id"),
	FOREIGN KEY("book_id") REFERENCES "Book"("book_id"),
	FOREIGN KEY("student_id") REFERENCES "Students"("student_id")
);

Activity 3

-- Customer table has no foreign keys

CREATE TABLE "Customer" (
	"customer_id"	INTEGER,
	"name"	TEXT NOT NULL,
	"email"	TEXT,
	"phone"	TEXT,
	PRIMARY KEY("customer_id" AUTOINCREMENT)
);

-- Product table has no foreign keys

CREATE TABLE "Product" (
	"product_id"	INTEGER,
	"name"	TEXT NOT NULL,
	"price"	REAL NOT NULL,
	"stock"	INTEGER NOT NULL,
	PRIMARY KEY("product_id" AUTOINCREMENT)
);

-- Table for foreign key exists

CREATE TABLE "Order" (
	"order_id"	INTEGER,
	"customer"	INTEGER NOT NULL,
	PRIMARY KEY("order_id" AUTOINCREMENT),
	FOREIGN KEY("customer") REFERENCES "Customer"("customer_id")
);

-- Tables of foreign keys exist

CREATE TABLE "Order Products" (
	"order_id"	INTEGER,
	"product_id"	INTEGER,
	"quantity"	INTEGER NOT NULL,
	"price"	REAL NOT NULL,
	PRIMARY KEY("order_id","product_id"),
	FOREIGN KEY("order_id") REFERENCES "Order"("order_id"),
	FOREIGN KEY("product_id") REFERENCES "Product"("product_id")
);

Activity 4

-- Customer table has no foreign keys

CREATE TABLE "Customer" (
	"customer_id"	INTEGER,
	"name"	TEXT NOT NULL,
	"address"	TEXT NOT NULL,
	PRIMARY KEY("customer_id" AUTOINCREMENT)
);

-- Item table has no foreign keys

CREATE TABLE "Item" (
	"item_id"	INTEGER,
	"name"	TEXT NOT NULL,
	"price"	REAL NOT NULL,
	PRIMARY KEY("item_id" AUTOINCREMENT)
);

-- Tables of foreign keys exist

CREATE TABLE "Orders" (
	"customer_id"	INTEGER,
	"item_id"	INTEGER,
	"date"	TEXT NOT NULL,
	PRIMARY KEY("customer_id","item_id"),
	FOREIGN KEY("customer_id") REFERENCES "Customer"("customer_id"),
	FOREIGN KEY("item_id") REFERENCES "Item"("item_id")
);

Movies Database

INSERT INTO movie
VALUES (1047, 'The Year of Living Dangerously', 1982, 115, 135);

INSERT INTO members
VALUES (5065, 'Emma Stone', 'Scottsdale, Arizona', NULL);

Schools Database

INSERT INTO teacher
VALUES ('Carter, N', 9, 'B4');

INSERT INTO results
VALUES (2230, 17, 50);

INSERT INTO subject
VALUES (19, "digital technologies", 'Carter, N')

Chinook Database

INSERT INTO artists (Name)
VALUES ('Imagine Dragons');

INSERT INTO albums (Title, ArtistId)
VALUES ('Evolve', 276);

INSERT INTO customers (FirstName, LastName, Company, City, Email, SupportRepId)
VALUES ('Zara', 'Lee', 'ZaraTech', 'Brisbane', 'zlee@example.com', 3);

-- Step 1
INSERT INTO playlists (Name)
VALUES ('Study Beats');

-- Step 2
INSERT INTO playlist_track (PlaylistId, TrackId)
VALUES (19, 3456);

-- Step 1
INSERT INTO customers (FirstName, LastName, Company, City, Email, SupportRepId)
VALUES ('Leo', 'Tran', 'TranTech', 'Melbourne', 'leo.tran@example.com', 4);

INSERT INTO invoices (CustomerId, InvoiceDate, BillingAddress, BillingCity, Total)
VALUES (61, '2025-07-30', '77 Innovation Rd', 'Melbourne', 39.95);

World Database

UPDATE city
SET Population = 2780063
WHERE CityName = 'Brisbane';

UPDATE city
SET CityName = 'Mumbai'
WHERE CityName = 'Bombay';

UPDATE language
SET Percentage = 92.0
WHERE CountryCode = 'ESP' AND Language = 'Spanish';

Shares Database

UPDATE industry
SET LongName = 'Computer Hardware & Peripherals'
WHERE Code = 3573;

UPDATE clients
SET City = 'Brisbane'
WHERE FirstName = 'Debra' AND Lastname = 'Parker' AND DOB = '1957-10-10';

UPDATE holdings
SET PurPrice = PurPrice * 0.9
WHERE PurDate = (
  SELECT MAX(PurDate)
  FROM holdings
);

Chinook Database

UPDATE customers
SET SupportRepId = (
  SELECT EmployeeId FROM employees
  WHERE FirstName = 'Jane' AND LastName = 'Peacock'
)
WHERE Country = 'Brazil';

UPDATE tracks
SET UnitPrice = UnitPrice + 0.20
WHERE GenreId = (
  SELECT GenreId FROM genres
  WHERE Name = 'Rock'
);

School Database

DELETE FROM results
WHERE percent < 50;

DELETE FROM results
WHERE stnumb IN (
  SELECT stnumb
  FROM student
  WHERE born < '2000-01-01'
);

Repairs Database

DELETE FROM repair
WHERE ready = 'Yes'
  AND date = '2010-06-03';

DELETE FROM repair
WHERE id_numb IN (
  SELECT id_numb
  FROM technicians
  WHERE grade = 'apprentice'
);

Chinook Database

-- First need to remove all invoice items to prevent conflict with invoice table
DELETE FROM invoice_items
WHERE InvoiceId IN (
  SELECT InvoiceId
  FROM invoices
  WHERE CustomerId IN (
    SELECT CustomerId
    FROM customers
    WHERE Country = 'Brazil'
  )
);

-- Then need to delete invoices to void conflict with customer table
DELETE FROM invoices
WHERE CustomerId IN (
  SELECT CustomerId
  FROM customers
  WHERE Country = 'Brazil'
);

-- Finally customers from Brazil can be deleted
DELETE FROM customers
WHERE Country = 'Brazil';

-- Remove from playlist_track first
DELETE FROM playlist_track
WHERE TrackId IN (
  SELECT TrackId
  FROM tracks
  WHERE AlbumId IN (
    SELECT AlbumId
    FROM albums
    WHERE ArtistId = (
      SELECT ArtistId
      FROM artists
      WHERE Name = 'Queen'
    )
  )
);

-- Remove invoice_items with those tracks
DELETE FROM invoice_items
WHERE TrackId IN (
  SELECT TrackId
  FROM tracks
  WHERE AlbumId IN (
    SELECT AlbumId
    FROM albums
    WHERE ArtistId = (
      SELECT ArtistId
      FROM artists
      WHERE Name = 'Queen'
    )
  )
);

-- Remove the tracks
DELETE FROM tracks
WHERE AlbumId IN (
  SELECT AlbumId
  FROM albums
  WHERE ArtistId = (
    SELECT ArtistId
    FROM artists
    WHERE Name = 'Queen'
  )
);

-- Remove the albums
DELETE FROM albums
WHERE ArtistId = (
  SELECT ArtistId
  FROM artists
  WHERE Name = 'Queen'
);

-- Finally, remove the artist
DELETE FROM artists
WHERE Name = 'Queen';