What is data compression and its types

data compression is a technology Which is modifying or encoding the bits of data in such a way that the size of the data is reduced, if put in simple words, the main work of data compression is to remove or replace the repeated data to reduce it.

Data compression helps to reduce the size of the storage of multiple data elements thereby providing more space to store the data and faster file sharing hence data compression is used in source coding or bitAlso known as -rate reduction.

Data compression is widely used in computing services and solutions such as digital media, computer networks, storage and backup Used in a variety of applications including systems, data compression works through a number of compression techniques and software that use data compression algorithms to reduce the size of data.

Lossless Data Compress is a type of data compression technique in which there is no loss of data and even after decompressing the original data, the data can be recovered without loss of data. Thus, examples of lossless data compress algorithms are run-length encoding, Huffman coding, arithmetic coding, and LZW (Lempel-Zive-Welch) compression, etc. Therefore, it is used where the data is very important, such as scientific data, text files, and medical images, etc.

Lossy data compression is also a type of data compression technique but in this there is loss of data and decompressed data cannot be recovered back so some data is lost to reduce the size of files.

Huffman coding is a lossless data compression algorithm widely used for compressing text data. This data compression technique was developed in 1952 by David A. was developed by Huffman.

In Huffman coding, each character in the file is assigned a variable-length code based on its frequency, so frequently occurring characters are assigned short codes, while less frequently occurring characters are assigned longer codes, and the end result is that storage space is used more efficiently and frequently occurring characters are represented using fewer bits.

For example, some steps are given below, so that you will know what are the rules of Huffman coding and it will be easy for you to understand it: –

Arithmetic coding is also a lossless data compression algorithm that encodes the entire file as a sequence of symbols in a single decimal number. It provides more efficient compression than traditional methods of Huffman coding. Arithmetic coding does the opposite of Huffman coding.

Thus, Huffman coding assigns a fixed length code to the characters, while in arithmetic coding a range of values ​​is assigned to the character, representing the file as a fraction between 0 and 1.

Let us now also know about its rules that how the file is encoded, so read the steps given below carefully: –

Data compression is widely used in various fields it has a wide range let us understand about its applications so some of the common applications of data compression are as follows:-

1. Use for storage compression – Data compression is used to reduce the data storage in the device so that the storage capacity is reduced, so we have to store a lot of data so that the storage becomes full. This is where data compression is used. For example, many data storage and database systems use data compression to store data so that the amount of disk space can be reduced.

2. Use for network compression – Data compression is used to reduce the amount of data transmitted over a network, thereby reducing the amount of bandwidth and increasing the speed at which data is transferred.

3. Use for file compression – Data compression is used to reduce the size of digital files because the size of digital files is very large and it takes a long time to transfer that is why data compression is used so compression algorithms are used to reduce the size of files in file formats such as ZIP, RAR and GZIP etc.

• Data compression techniques reduce the size of data so that many data files can be easily stored.
• It reduces the size of the file which enables faster file transfer over the internet.
• When data is compressed, it takes up less space in memory and the performance of memory-dependent systems such as databases and web servers can be improved.
• Being data compressed, the data takes up less space, which makes backup and recovery easier, usually easier for large amounts of data.
• There are many such data compression tools which are easy to use and these tools are user friendly.
• Compressed data can be read and written faster than the original data.

• You need a suitable program to decompress or uncompress the downloaded data compress file back, so many times such program systems are not available to the user on the internet, causing trouble to the user.
• Compressing large files takes excessive time due to which the performance of the system slows down.
• Compression algorithms that use lossy compression can result in loss of data quality or resolution, as well as Videocan be problematic for audio and image files.