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  2. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    In these schemes, some loss of information is accepted as dropping nonessential detail can save storage space. There is a corresponding trade-off between preserving information and reducing size. Lossy data compression schemes are designed by research on how people perceive the data in question.

  3. Smallpdf.com - Wikipedia

    en.wikipedia.org/wiki/Smallpdf.com

    The idea came from the need for their families to compress and send large documents via email. [5] The initial version of the site featured a standalone PDF compression tool. [6] Since then, the online platform has introduced over 16 PDF tools to convert, compress and edit PDF documents. [7]

  4. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    By operation of the pigeonhole principle, no lossless compression algorithm can shrink the size of all possible data: Some data will get longer by at least one symbol or bit. Compression algorithms are usually effective for human- and machine-readable documents and cannot shrink the size of random data that contain no redundancy. Different ...

  5. Why Small Businesses Are Important to Our Economy and ... - AOL

    www.aol.com/why-small-businesses-important...

    At the heart of America's growth and prosperity are small businesses. Small and mighty, these businesses are vital not only to our communities, but at a broader economic level. See Our List: 100...

  6. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    In contrast, lossy compression (e.g. JPEG for images, or MP3 and Opus for audio) can achieve much higher compression ratios at the cost of a decrease in quality, such as Bluetooth audio streaming, as visual or audio compression artifacts from loss of important information are introduced. A compression ratio of at least 50:1 is needed to get ...

  7. Run-length encoding - Wikipedia

    en.wikipedia.org/wiki/Run-length_encoding

    Run-length encoding (RLE) is a form of lossless data compression in which runs of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from ...

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