What Is Data Compression?

These days, Data compression is used everywhere. In Mp3, mp4, RAR, zip, jpg, and png files or many files that all use compressed data. Data compression Convert large files into much smaller ones.


Data compression is the process of modifying, encoding or converting the bits structure of data in such a way that it consumes less space on disk. It enables reducing the storage size of one or more data elements. source coding or bit-rate reduction are names of Data Compression.

Need for Compression

as we all know that Digital Communication is have more advantage over Analog Communication. So mostly, we are store data in Digital formate. We are storing data in Documents, Images, Videos, Audio or more. Without data compression, a 3-minute song would be over 100Mb and a 10-minute video would easily be over 1Gb.

But when we used these types of uncompressed and large data that require the massive amount of data storage. as data storage grows, the access time for retrieving data increase.

so for that, we need to Data compression to reduce the size of data for storage. Data compression is important at this age. It makes the transfer of data relatively easy.

A common data compression technique removes and replaces repetitive data elements and symbols to reduce the data size.

Types of Compression

in some case when information is compressed, the redundancies are removed, but sometimes this is not sufficient to reduce the size of data. So in such a way, real information also removed in such a way that it affects the quality of the result then its ok.

but some case, compression is not main but the main is real information. So at the time of retrieve, we can retrieve exact real information. On this basis There are two general types of compression :

1) Lossy Compression

2) Lossless Compression

Lossless Compression:-

as name, in lossless compression data is not altered or lost in the process of compression or decompression. Decompression generates an exact replica of the original data. In this compression, we cannot afford to misplace even a single bit of information.

in this type of compression usually, it reducing the repeated character to a count. Here, We decompressed the repeated character, there is no loss of information in this approach.

thus lossless compression is good for text data and repetitive data in images like the binary image, gray-scale images.

Lossless compression techniques have been able to achieve the reduction in size in the range of 1/10 to 1/50 of original uncompressed size.

Lossy Compression:-

Lossy compression attempt to eliminate redundant or unnecessary information. Most video compression technologies, such as MPEG, use a lossy technique.

lossy compression is used for compressing audio, color images and video in which absolute data accuracy is not essential. Like video file decompressed on a frame by frame basis, the loss of data in one frame will not be perceived by the eye.

the most important reason using the lossy compression method is they can achieve much better compression ratio.

Comparision: Lossy Vs Lossless Compression

  • in Lossless copression original data=compressed data, where in lossy compression original data!=compressd data.
  • Lossless compression obtains less compression ratio, where lossy compression obtains much higher compression ratio than lossless.
  • The lossless compression used in applications such as text file compression, where The lossy compression obtains much higher compression ratio than lossless.
  • There is Minimum support for lossless formats. Loosy formates have better support among different types of a Media player than lossless formats.
  • The quality of file in Lossless compression preserves the exact same that was present in the original source. in Lossy Compression, Substantial loss in quality with every successive conversion.


my final word is we can achieve data compression by many techniques. we can achieve Lossless compression by Huffman coding, pack bits coding, Run-length coding, LZW, LZ77, LZ78 or more. we can achieve Lossy compression by joint photographic, fractal compression, CCITT H.261 and more.

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