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5 Examples of Compression

 , updated on January 15, 2023
Compression is the conversion of data to a format that requires less storage space as measured in bits. This typically involves looking for patterns in data and eliminating redundancies. As such, how well something compresses depends on how many patterns can be found in data. Text often compresses well due to patterns such as words. Data that is already compressed or that is highly random doesn't compress much. The following are a few examples of data compression.

Audio

Common audio formats include both lossless compression formats such as FLAC and lossy formats such as MP3. Lossy compression results in the loss of small amounts of information meaning a slight decline in audio quality.

Images

Digital cameras typically store images as compressed files automatically. Some cameras also allow raw image files to be stored that are uncompressed or slightly compressed. Depending on the speed of storage media, this can slow a camera down because raw images are extremely large. As such, storage in a lossy format such as JPEG is far more common.

Disk Compression

It is common for data to be compressed at the operating system level. For example, all data on a storage device can be automatically compressed by an operating system. With compression, there is a tradeoff between processing speed and disk usage whereby compressed files have slower access times.

Communications

Compressing messages sent over networks can improve performance of tools such as web browsers or mobile apps by efficiently using available bandwidth. Data compression can also lower a user's telecom bills if they are charged by data usage.

Archive Files

Archive files allow multiple directories and files to be placed in a single file. Common archive file formats such as ZIP also compress data. Archive files are commonly used for creating backups and sharing data.
Overview: Compression
Type
Definition
The conversion of data to a format that requires less space as measured in bits.
Value
Conserving resources such as data storage and bandwidth.
Trade-offs
Compression consumes computing cycles. Generally speaking, it is slower to access compressed data.
Lossy compression algorithms result in the loss of information and can reduce the quality of media such as audio files and images.
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