Notes for A.2.11 Evaluating Data Types - IB | RevisionDojo
A.2.11 Evaluating Data Types Notes
Importance of Data Type Selection
The choice of data type directly influences how data is stored, processed, and interpreted.
Selecting the wrong data type can lead to:
Data loss
Inefficient memory usage
Security vulnerabilities.
Example
If you store a phone number as an integer, leading zeros may be lost (e.g., 0123456789 becomes 123456789).
Using a string preserves the original format.
Exam technique
Try to remember the high-level information of choosing one data type over another through the content below.
You are not expected to memorise all of it!
Factors to Consider When Choosing Data Types
1. Nature of the Data
Quantitative Data:
Integers: Used for whole numbers (e.g., age, quantity).
Floating-Point Numbers: Used for decimal values (e.g., temperature, price).
Qualitative Data:
Strings: Used for text-based data (e.g., names, addresses).
Booleans: Used for binary choices (e.g., true/false, yes/no).
Categorical Data:
Enumerations: Used for predefined categories (e.g., days of the week, product types).
Example
Storing a student's grade as a string ("A", "B", "C") is more appropriate than using an boolean, as grades are categorical.
2. Precision and Accuracy
Precision: The number of significant digits a data type can represent.
Accuracy: How closely the stored value matches the real value.
Example
Floating-point numbers are suitable for scientific calculations but may introduce rounding errors.
Decimals are preferred for financial data to ensure exact calculations.
3. Memory Efficiency
Different data types consume varying amounts of memory.
Choosing a more efficient data type can optimize system performance.
Example
Using a byte (8 bits) to store values between 0 and 255 is more efficient than using an integer (32 bits) for the same range.
4. Data Validation and Integrity
The chosen data type should align with the expected data format to prevent invalid entries.
Booleans restrict values to true/false, reducing the risk of invalid data.
Example
Storing a date as a string allows invalid entries like "32/13/2023".
Using a date data type enforces valid date formats.
5. Security and Privacy
Sensitive data should be stored in a way that minimizes exposure to unauthorized access.
Hashing or encrypting data types can enhance security.
Example
Storing passwords as plain text strings is insecure.
Using hashed data types protects user credentials.
6. End-User Needs
The data type should support the intended use cases and user interactions.
Strings are user-friendly for displaying information, while integers are better for calculations.
Example
Displaying a phone number as a string allows formatting (e.g., (123) 456-7890), enhancing readability for users.
7. Stakeholder Requirements
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Note
Introduction to Data Types
Data types are fundamental building blocks in programming that define the nature of data and how it can be manipulated.
They provide a way to categorize and organize data, ensuring that operations are performed correctly and efficiently.
DefinitionData TypeA classification that specifies which type of value a variable can hold and what operations can be performed on it.AnalogyThink of data types as different containers in a kitchen. Just as you wouldn't store soup in a bread box, you shouldn't store text in a numerical data type.ExampleCommon data types include integers (whole numbers), floats (decimal numbers), strings (text), and booleans (true/false values).
