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A3 · Data Processing
Spec reference: Section A3 - Hardware and Software Key idea: Understand how computer systems collect, process and store data, and the implications for individuals and organisations.
What is data processing?
Data processing is the collection and manipulation of data to produce meaningful information. Computer systems are used because they can process large volumes of data quickly, accurately, and consistently.
The role of hardware in collecting data
Hardware devices are used to capture data automatically or manually:
| Hardware | Data collected |
|---|---|
| Keyboard/mouse | User input |
| Barcode scanner | Product codes in retail and warehouses |
| RFID reader | Contactless identification (stock, access cards) |
| Sensors (temperature, motion) | Environmental data in IoT systems |
| Webcam/microphone | Video and audio for surveillance or conferencing |
| Touchscreen | Touch input in kiosks, phones, tablets |
The role of software in collecting data
Software controls how data is captured and stored:
- Web forms: Capture user data through browsers.
- Database front-ends: Allow structured data entry into records.
- APIs: Allow systems to receive data from external sources.
- Logging software: Automatically records events and system activity.
Data processing functions
| Function | Description | Example |
|---|---|---|
| Aggregation | Combining multiple data items into a summary | Calculating total sales across all branches |
| Analysis | Identifying patterns and trends in data | Spotting which products sell best in winter |
| Conversion | Changing data from one format to another | Converting CSV to XML |
| Reporting | Producing structured summaries of data | Generating a monthly sales report |
| Sorting | Arranging data in a specified order | Alphabetical order, highest to lowest |
| Validation | Checking data meets defined rules before processing | Ensuring an age field contains a number in range |
Backup and data recovery procedures
Regular backups protect against data loss from hardware failure, ransomware, accidental deletion, or disasters.
Backup types
| Type | What it backs up | Speed | Storage needed |
|---|---|---|---|
| Full backup | Everything | Slow to create | Most storage |
| Incremental backup | Changes since last backup of any type | Fastest to create | Least additional storage |
| Differential backup | Changes since the last full backup | Medium | Medium |
Good backup practice (3-2-1 rule)
- 3 copies of data
- 2 different storage types (e.g. local drive + cloud)
- 1 offsite copy
Impact on individuals and organisations of storing data across multiple systems
| Factor | Implication |
|---|---|
| Access | Data can be accessed from multiple locations; risk of unauthorised access increases |
| Cost | Hardware, software licences, and cloud storage all carry costs |
| Implementation | Migration, testing, and training take time and resource |
| Productivity | Centralised data can improve collaboration; poor systems can slow work down |
| Security | More systems mean a larger attack surface; data breaches become more complex to manage |
Exam point
When discussing implications in the exam, always give both the benefit and the risk. For example: storing data in the cloud improves access from anywhere, but increases the risk of data interception if not encrypted.
Summary
| Term | Meaning |
|---|---|
| Aggregation | Combining data items into a summary value |
| Incremental backup | Backs up only data changed since the last backup |
| Validation | Checking data against rules before it is accepted |
| RAID | Protects data through redundancy across multiple drives |
| 3-2-1 rule | 3 copies, 2 media types, 1 offsite |