Data Organisation and Data Control

Data organisation and control are essential to ensure that information in a computer system is structured efficiently, can be accessed effectively, and remains accurate and secure. This topic explores the hierarchical organisation of data, methods of accessing data, and techniques to control errors.

1. Hierarchical Organisation of Data

Data in a computer system is organised in a hierarchy from the smallest unit to the largest:

1. Data

• Raw facts or values (e.g., a single student’s name, a number, or a measurement).

2. Field

• A single characteristic of a record, consisting of one or more related data items.

• Example: “Student Name” or “Test Score” fields in a student database.

3. Record

• A complete set of fields representing a single entity or item.

• Example: A student record containing Name, ID, Date of Birth, and Grade.

4. File

• A collection of related records stored together.

• Example: A file of all students in a class.

5. Database

• A structured collection of files that allows efficient storage, retrieval, and management of data.

• Example: A school database containing files for students, teachers, and courses.

Remark: Understanding this hierarchy helps students grasp how data is organised systematically, making retrieval and processing efficient.

2. Organisation, Storage, and Retrieval of Records

Records can be organised and accessed in different ways:

a. Sequential Access

• Definition: Records are accessed one after another in order.

  • Simple to implement.

  • Efficient for processing all records in sequence.

• Advantages:

• Disadvantages:

  • Slow when searching for a specific record.

  • Not suitable for large databases where frequent random access is required.

• Applications:

  • Payroll systems, log files, or transaction processing where all records are processed regularly.

b. Direct (Random) Access

• Definition: Records can be accessed directly using a unique key or address.

  • Fast access to specific records.

  • Efficient for large databases where certain records are frequently retrieved.

• Advantages:

• Disadvantages:

  • More complex to implement.

  • Requires a unique identifier or index.

• Applications:

  • ATM systems, library catalogues, airline reservation systems.

3. Data Control

Data control ensures the accuracy, reliability, and security of data in a system. Key needs include:

• Preventing data entry errors.

• Ensuring that only authorised users can access and modify data.

• Maintaining consistency and integrity across the database.

• Enabling recovery from errors or failures.

Example:

• Password protection for accessing student grades.

• Audit trails to track changes in financial records.

4. Error Detection and Prevention

Errors can occur during data entry, transmission, or storage. Techniques to detect and prevent errors include:

a. Validation

• Definition: Checking the data entered against rules to ensure it is reasonable and acceptable.

  • A student age field only allows numbers between 3 and 100.

  • Ensures that text is entered where text is expected.

• Example:

b. Parity Checking

• Definition: Adding an extra bit (parity bit) to binary data to detect errors during transmission or storage.

• Types: Even parity and odd parity.

• Example: Sending 1011001 with an extra parity bit to ensure an even number of 1s.

c. Verification

• Definition: Checking that data entered matches the original source.

  • Double-entry of a password to ensure consistency.

  • Scanning a form twice to verify accuracy.

• Example:

d. Prevention by Validation and Verification

• Errors can be minimised by combining validation rules and verification processes during data entry.

• Example: Online forms that check email format, required fields, and password confirmation.

5. Summary

• Data is organised hierarchically: Data → Field → Record → File → Database.

• Records can be accessed sequentially or directly, each with advantages and disadvantages.

• Data control is essential to maintain accuracy, reliability, and security.

• Errors can be detected using validation and parity checking, and prevented using verification and proper validation techniques.

• Understanding data organisation and control is fundamental for efficient information management in modern computing systems.