A-Level Computer Science Revision — Data Compression
Revise Data Compression for A-Level Computer Science with a topic explanation, worked example and common mistakes. Check the board notes for specification differences.
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What is Data Compression?
Data compression is the process of reducing the number of bits needed to represent data. It is used to save storage space and to reduce the time it takes to transmit data. There are two main types of compression: lossless and lossy.
Board notes: AQA, Edexcel, and OCR all cover data compression. Students should be able to explain the difference between lossless and lossy compression and give examples of each.
Step-by-step explanationWorked examples
Worked example
Run-length encoding (RLE) is a simple form of lossless compression. The string 'AAABBC' could be encoded as '3A2B1C'. This reduces the storage from 6 characters to 6, but for longer runs it is more effective. For example, 'AAAAAAAAAA' becomes '10A'.
Practise this topic
Start with low-focus cards for Data Compression, then move into full exam-style practice when you want the heavier session.
Common mistakes
- 1Confusing lossless and lossy compression.
- 2Not understanding the trade-off between compression ratio and quality (for lossy compression).
- 3Incorrectly applying a compression algorithm, such as run-length encoding.
Data Compression exam questions
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Frequently asked questions
When would you use lossy compression?
Lossy compression is used when some loss of quality is acceptable, for example, with images, audio, and video. The goal is to achieve a much smaller file size than with lossless compression.
What is Huffman coding?
Huffman coding is a lossless data compression algorithm. It assigns variable-length codes to input characters, with shorter codes assigned to more frequent characters. This results in a smaller overall representation of the data.