The power of data: Using data modelling Chapter Notes | IGCSE Cambridge Computing for Year 6 - Class 6 PDF Download

Data models, simulations and real-life scenarios

• Computer Models: These are digital versions of real-world situations. They use data to mimic what happens in real life. For example, a computer model can help you figure out if you have enough money to buy something.

• Creating Models: We use software or special programs to create these models. They follow certain rules, which are written in programming languages, to work correctly.

• Spreadsheets: A simple way to make a model is by using a spreadsheet application. Here, you label each part of the model and enter data. Formulas in the spreadsheet help connect these parts.

• Example - Birthday Party Costs: Imagine you’re planning a birthday party and you have a budget of $100. You list all the items you need, like pizza and balloons, and their prices. The spreadsheet helps you calculate the total cost and how much money you’ll have left after buying everything.

• Factors and Formulas: In our party example, factors include the items you need and their prices. Formulas help calculate the total cost and the remaining budget. For instance, to find the total cost, you’d use a SUM formula like this: 

  SUM=Item 1 Price+Item 2 Price+…

• Databases: These are used for more complex models. A database organizes data into tables with headings like username, password, and email.

• Simulations: These are advanced models that often include graphics to visually represent a situation. For example, a flight simulator lets pilots practice flying without the risks of being in the air.

• Uses of Models and Simulations:

  • Medicine: Doctors use data models to diagnose illnesses quickly.
  • Training: Pilots use simulators to safely learn how to fly planes.
  • Science: Researchers predict outcomes, like how temperature changes affect nuclear reactions.
  • Weather: Meteorologists use models to forecast weather changes.
  • Business: Companies analyze sales data to predict future stock needs.

• Pros and Cons of Simulations:

  • Pros: They’re safe for training, can model many scenarios, and are cheaper than real equipment.
  • Cons: They can be costly to create and might not cover every possible outcome.

Spreadsheets: Using Microsoft Excel

• MS Excel: This is an example of a spreadsheet application. It helps organize data in rows and columns. Each cell in a spreadsheet can contain text, numbers, or formulas.
• Worksheets: Excel files have worksheets, which consist of cells arranged in rows and columns. These cells are labeled with numbers and letters.
• Calculations: Spreadsheets are perfect for quick calculations. They start as simple tables with words and numbers, but they become more powerful when you add formulas to link the data.
• Cells and Cell References:
• Each box in a worksheet is called a cell.
• Cells can contain text, numbers, or formulas.
• Cell references (like D3) help identify each cell. For example, cell D3 is colored bright blue in the spreadsheet below.
• Formulas and the Formula Bar:
• Formulas are like math equations. They use numbers, cell references, and math symbols.
• To add a formula, type it into the formula bar (which starts with an equals sign, like =SUM(A1:A3)).
• Functions:
• Excel has built-in functions like SUM (adds up numbers) and AVERAGE (calculates the average of a group of numbers).
• Formulas can include these functions to perform more complex calculations.
• Formatting:
• You can change how text looks in Excel using tools similar to those in word processors.
• For example, to make text bold, select the cells and click the bold button (B).

Modelling tools: Conditional formatting

• Spreadsheet applications allow users to format data using conditional formatting. This can be useful if you want to highlight important data.
• You could do this in a number of ways. For example, in our school trip model we could set the cells in column M to green if the balance for a student is 0.

Databases: Using Microsoft Access

• MS Access: This is a database application used to store and organize data that represents real-world scenarios.
• Table Structure: In MS Access, data is stored in tables. These tables have field headings which are special titles for each column.

• Data Types: Each piece of data is given a data type which tells MS Access what kind of information it is. Here are some examples:

  • Text: For words or a mix of letters and numbers, not used in calculations.
  • Number: For data that will be used in calculations, like integers or decimals.
  • Date/Time: To record dates or times, with different formats available.
  • Currency: For money values, with options for different currencies like dollars.
  • Autonumber: A unique number assigned to each record, which helps identify them.
  • Yes/No: For data that has only two options, like true/false or yes/no.
• Field Size: MS Access can set aside space for data, like 255 characters for text. But you can change this to save space, like setting a surname field to only 30 characters.
• Primary Key: This is a special field added to make sure each record is unique. It’s often an autonumber so each new record gets a new number automatically.
• Identifying Records: In a large database, it’s important to find the right record. For example, if two students have the same name, they can be told apart by their StudentID.

Database models: Setting up your data model

Database Table: Imagine you’re creating a table to store information about competitors in a gaming competition. Each column in the table is called a field.

Field Names and Data Types: Each field has a name and a type of data it will store. Here’s what each field might represent:

1. StudentID: This is an Autonumber field, which means it will automatically give each competitor a unique number.
2. Surname and Firstname: These are Short text fields, used for names because they’re made of letters and not used in calculations.
3. Stage: Also a Short text field, even though it has a number (like Stage 7), because you won’t use it for calculations.
4. DOB (Date of Birth): This is a Date/Time field because it stores dates.

Choosing Data Types: It’s important to choose the right data type because it determines what you can do with the data. For example:

1. If a field is set to Text, you can’t use it for math calculations.
2. If a field is set to Number, you can add, subtract, and do other math operations.

Why It Matters: Picking the correct data type helps ensure that the database works properly and that you can do the right kind of processing with each piece of data.

Collecting user data

1. Purpose: Data capture forms are used to gather information before it’s entered into a database. They help ensure that data is collected in the right format.

2. Design Elements:

   • Labels, Spaces, Boxes: These guide the user on what information to enter and where.
   • Tick Boxes: Provide clear options for users to choose from.
   • Example Data: Sometimes included to show users how to fill in their information correctly.

3. MS Access Forms: In MS Access, form designers can add text boxes with additional instructions or example data to help users fill out the form accurately.

4. Personal Details Section: This part of the form collects essential information like first name, surname, date of birth, gender, and hobbies. It’s laid out clearly so users know exactly what to provide.

5. User-Friendly Design: A good form is easy to understand and complete. It should have:

   • Clear instructions.
   • A description of why the data is being collected.
   • The name of the organization collecting the data.
   • A graphic or logo related to the form’s purpose.
   • Appropriately sized response boxes.
   • A layout that corresponds to the database fields.
   • Examples for guidance.
   • Multiple-choice options where suitable.

6. Completion Methods:

   • Online: Data goes directly into the database under the correct field headings.
   • Paper: Data must be manually typed into the database.

Searching for the answers

1. Purpose of Queries: Queries are tools used in databases to find and select specific data. They help answer questions by filtering data based on certain conditions.

2. Criteria: When you create a query, you set criteria which are like rules that the data must match to be included in the search results. For example, if you want to find all students in Stage 7, your criterion would be “Stage = 7”.

3. Planning Queries: Database developers need to know what kinds of searches will be done so they can design the database to handle those queries effectively.

4. Comparison Operators: These are symbols used in criteria to compare data, such as:

   • > (greater than)
   • < (less than)
   • = (equal to)

5. For instance, if you want to find students older than 11, you’d use “age > 11”.

6. True or False: The result of applying a comparison operator is always either TRUE or FALSE. If a student’s age is 12 and the criterion is “age > 11”, the result is TRUE because 12 is greater than 11.

7. Example Queries: Here are some examples of queries you might run on a student database for a gaming competition:

   • Query: Find all students in class 7T2.
     • Criteria: “Class = 7T2”
     • Result: Lists details of all students in class 7T2.
   • Query: List the names and dates of birth of students in class 7T3.
     • Criteria: “Class = 7T3”
     • Result: Shows the first name, surname, and date of birth for students in class 7T3.

Highlighting the important data

• Data models are often used to help organisers and managers make decisions. 
• To help make decisions quickly, the important data must be easy find. 
• To help with this, you can use a featu re in MS Access called conditional formatting to highlight the really important areas. 
• To do this, you need to set rules so that data that matches those rules is automatically highlighted.

Modelling methods: Software choices

1. Databases:

   • Organize Data: They use field headings and tables for clarity.
   • Queries: Allow searching of data to find answers.
   • Forms: Provide a user-friendly interface for data entry.
   • Primary Keys: Ensure each data item is unique.
   • Data Types: Define how data is stored and displayed.
   • Conditional Formatting: Highlights data based on specific conditions.

2. Spreadsheets:

   • Cell Storage: Data is stored in individual cells within a grid.
   • Labels: Help organize and clarify data.
   • Data Types: Enhance data formatting.
   • Formulas: Perform calculations and link data items.
   • Conditional Formatting: Also available to spotlight data meeting certain criteria.

Both databases and spreadsheets offer conditional formatting to visually emphasize data that fulfills set conditions, making them both valuable tools for data analysis and decision-making. The choice between the two often depends on the specific needs of your project, such as the complexity of data, the volume of data, and the types of operations you need to perform