> For the complete documentation index, see [llms.txt](https://www.csprinciples.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.csprinciples.com/big-idea-2/2.2-data-compression.md).

# 2.2 Data Compression

## Enduring Understanding

The way a computer represents data internally is different from the way the data are interpreted and displayed for the user. Programs are used to translate data into a representation more easily understood by people.

## Learning Objective

Compare data compression algorithms to determine which is best in a particular context. 

## Essential Knowledge

Data compression can reduce the size (number of bits) of transmitted or stored data.

Fewer bits does not necessarily mean less information.

The amount of size reduction from compression depends on both the amount of redundancy in the original data representation and the compression algorithm applied.

Lossless data compression algorithms can usually reduce the number of bits stored or transmitted while guaranteeing complete reconstruction of the original data.

Lossy data compression algorithms can significantly reduce the number of bits stored or transmitted but only allow reconstruction of an approximation of the original data.

Lossy data compression algorithms can usually reduce the number of bits stored or transmitted more than lossless compression algorithms.

In situations where quality or ability to reconstruct the original is maximally important, lossless compression algorithms are typically chosen.

In situations where minimizing data size or transmission time is maximally important, lossy compression algorithms are typically chosen.


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