Data Compression – A Level Computer Science AQA Revision

Data Compression refers to the process of reducing the amount of data required for the storage or transmission of information.
It helps in saving storage space, speeds up file transfer, and can improve information processing performance in many scenarios.

Data compression involves two primary methods, namely Lossless Compression and Lossy Compression.

Lossless Compression is a type of data compression that involves no loss of original information after decompression.
It is commonly used for scenarios requiring exact reproduction, such as text, programming code, and certain types of imaging and multimedia.
Common examples include ZIP files and GIF images.
Techniques for lossless compression include Run-Length Encoding, Huffman Coding, and the Lempel-Ziv (LZ-77) algorithm.

Lossy Compression, in contrast, eliminates “unnecessary” bits of information and reduces data size significantly, which could result in a loss in quality.
This method is predominantly useful for audio, video, and image files, where a slight loss of quality is not as noticeable.
A well-known example is the MP3 audio format and JPEG format for images.
Techniques include quantization, used to reduce the precision of certain types of data, and transform coding, which converts the data into a representation that can be more efficiently compressed.

The Compression Ratio is a measure utilised to evaluate the efficiency of a data compression algorithm. It is calculated as the size of the compressed data divided by the original data size.

Data compression plays a crucial role in efficient storage and transfer of data, allowing for more effective use of storage space and transmission bandwidth.
In computer systems, data compression is often implemented in the file system, network transmission, and certain types of software such as media players and web browsers.