2.2 Data Compression

Why compress data?

Data compression shrinks file size, saving storage space and reducing time needed to transmit data over networks. Compression algorithms convert data into a more compact representation before storage/transmission, then a corresponding algorithm restores it when needed. Smaller files mean faster uploads, downloads, and streaming, especially on limited bandwidth.

Lossless vs. lossy compression

Lossless compression reduces file size while allowing the *exact* original data to be reconstructed — critical for text or program files where every bit matters. Lossy compression permanently discards some data to shrink files further, trading some fidelity (quality/precision) for a much smaller size — common in images, audio, and video where minor loss is imperceptible.

Compression trade-offs

Compression involves trade-offs between file size, fidelity, and processing/transmission time. Higher compression usually means smaller files but slower processing or lower quality. Choosing lossless vs. lossy depends on the data's purpose: a legal document needs lossless compression, while a casual photo can tolerate lossy compression for a smaller file.

Key terms

Data compression

The process of reducing the size of data to save storage space or transmission time.

Lossless compression

Compression that allows the original data to be perfectly reconstructed with no loss of information.

Lossy compression

Compression that permanently removes some data, reducing fidelity in exchange for a smaller file size.

Fidelity

The degree to which compressed data retains the quality/precision of the original data.

Compression trade-off

Balancing smaller file size against fidelity and processing/transmission time when choosing a compression method.

Try an AP-style question

Using run-length encoding, how might "AAAABBBCC" be compressed?

1. ABC
2. 9ABC
3. A4B3C2A
4. 4A3B2C