In computer science and information theory, data compression or source coding is the process of encoding information using fewer bits (or other information-bearing units) than an unencoded representation would use through use of specific encoding schemes. For example, this article could be encoded with fewer bits if we accept the convention that the word "compression" be encoded as "comp". One popular instance of compression that many computer users are familiar with is the ZIP file format, which, as well as providing compression, acts as an archiver, storing many files in a single output file.

As is the case with any form of communication, compressed data communication only works when both the sender and receiver of the information understand the encoding scheme. For example, this text makes sense only if the receiver understands that it is intended to be interpreted as characters representing the English language. Similarly, compressed data can only be understood if the decoding method is known by the receiver. Some compression algorithms exploit this property in order to encrypt data during the compression process so that decompression can only be achieved by an authorized party (eg. through the use of a password).

Compression is possible because most real-world data has statistical redundancy. For example, the letter 'e' is much more common in English text than the letter 'z', and the probability that the letter 'q' will be followed by the letter 'z' is rather small. Lossless compression algorithms usually exploit statistical redundancy in such a way as to represent the sender's data more concisely, but nevertheless perfectly.

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Lynch: #CNI09f Compressed data is great w/ grnteed loss-less compression & perfect disk - difference between flipped pixel & inoperable file
TAC_NISO (Todd Carpenter) Mon, 14 Dec 2009 18:55:40 -0000
Lynch: #CNI09f Compressed data is great w/ grnteed loss-less compression & perfect disk - difference between flipped pixel & inoperable file
Variable-length Codes for Data Compression: Springer | 2007-10-01 | ISBN: 1846289580 | 196 pages | PDF | 1,72 M.. http://bit.ly/5LVg1e
agungabb (agungabb) Mon, 14 Dec 2009 15:17:22 -0000
Variable-length Codes for Data Compression: Springer | 2007-10-01 | ISBN: 1846289580 | 196 pages | PDF | 1,72 M.. http://bit.ly/5LVg1e
and now, to study compression and huffman encoding (topic we didn't seem to do in our data structures class)
p10q (tom harada) Mon, 14 Dec 2009 07:15:41 -0000
and now, to study compression and huffman encoding (topic we didn't seem to do in our data structures class)
Finished my dictzip classes, allowing for transparant compression of data through istream/ostreams.
danieldekok (Daniel de Kok) Sun, 13 Dec 2009 13:53:38 -0000
Finished my dictzip classes, allowing for transparant compression of data through istream/ostreams.
@bretupdegraff you can often not get a lot of compression out of it, so the space savings can be negligible. Depends on data. #SQL #SQLPASS
aaronbertrand (Aaron Bertrand) Sun, 13 Dec 2009 00:06:33 -0000
@bretupdegraff you can often not get a lot of compression out of it, so the space savings can be negligible. Depends on data. #SQL #SQLPASS
Hadoop at Twitter (part 1): Splittable LZO Compression » Cloudera Hadoop & Big Data Blog http://bit.ly/4FZVnO
BrianGolbere (Brian Golbere) Fri, 11 Dec 2009 19:43:13 -0000
Hadoop at Twitter (part 1): Splittable LZO Compression » Cloudera Hadoop & Big Data Blog http://bit.ly/4FZVnO

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