What is data compression and its types

today’s Internet In this era, we all do our work mostly with mobile, laptop, computer devices, in such a situation, we store more and more data and there are many such files which have to be shared, but due to the large size of the data, the storage capacity becomes very less and it is difficult for anyone to share the file, so here it comes to the point. This is a technology of data compression, which makes the data smaller.

Today in this article we will know that What is data compression and its types What Is Data Compression And Its Types In Hindihow it works, what are its uses, what are its advantages and disadvantages, etc. All the information related to it will be given to you in this post, so read this article till the end to know about data compression technology.

Read this also – What is E-Tree in data structure and what are its uses

what is data compression What Is Data Compression

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.

data compression types Types Of Data Compression

There are two types of data compression techniques, lossless data compression and lossy data compression. Let us now understand in detail what these two are: –

1. What is Lossless Data Compression What Is Lossless Data Compression

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.

2. What is Lossy Data Compression

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.

lossy data compression algorithm Examples are Discrete Cosine Transform (DCT), Fractal Compression, Transform Coding and MPEG (Motion Picture Experts Group) compression Lossy compression etc. and is used where some amount of data loss is acceptable such as audio, video and image files etc.

Popular Data Compression Techniques Popular Data Compression Techniques

Many data compression techniques are used, here I have told you about some popular techniques which are as follows: –

1. Huffman Coding

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: –

First of all, each frequency present in the file is counted.
After that a binary tree is created as a leaf node.
Then each branch is assigned as 0 or 1 starting from the root of the tree.
The assigned code is used to encode the text file.
So finally binary tree is used to bring the encoded text file back to its original form.

3. Arithmetic Coding

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: –

First the frequency of each character is determined in the file.
After that each character is calculated on the basis of frequency.
Then after that the initial range is set as (0,1).
The class is then updated (having new parts or new information) based on the probabilities for each character in the files.
Hence the last category is encoded using binary representation.
The final range is used to decode the encoded files.

if both arithmetic coding and huffman coding algorithm Speaking of arithmetic coding, it is slightly more complex than Huffman coding but it provides better compression results usually for text data with a large number of unique characters.

Data Compression Applications Data Compression Applications

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.

In addition, data compression techniques are used to reduce the size of audio, video and image files so that data can be easily stored and transferred. Overall, data compression techniques are used everywhere in the computing field and play an important role in reducing the bandwidth for transmitting data across networks.

Advantages of Data Compression Advantages Of Data Compression

Data compression has the following advantages:-

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.

Disadvantages of Data Compression Disadvantages Of Data Compression

Along with the advantages of data compression, it also has some disadvantages which are as follows:-

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.

Data Compression FAQ FAQs On Data Compression

Q1. Why is data compression important?

Answer – Data compression is important because it provides us more storage by reducing the size of data and it is easy to transfer files and also less time is taken in data processing and more time to do our work. Data compression is important because of all these reasons.

Q2. How are data files compressed?

Answer – To compress data files, you must use a compression tool or program such as WinZip, 7-Zip, or Gzip, etc. All these tools use an algorithm to reduce the size of the data file.

Therefore, to compress the file, you have to choose a program, after that select the “Compress” or “Zip” option from the program’s menu, and double-click the file to decompress it. One more thing to note here is what type of data compression technique do you use, lossless data compression or lossy data compression.

what have you learned What have you learned

In this article, you learned what is data compression, its types, what are its advantages and disadvantages, etc. Overall, data compression technology is very important for us because a lot of data is present in large numbers, due to which it is difficult to store and transfer.

I hope that this information given by me will be very important for you, if you have any question related to this, then do tell us by commenting.

So, if you liked this post, then definitely share it with your friends so that everyone can get information about data compression technology and in the same way, read our website to learn information related to technology. Thank you.

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