What is data compression?
Data compression is a technique used to reduce the amount of data needed to represent a given piece of information. This is important because it allows for more efficient storage and transmission of data, which can save space and bandwidth.
There are two main types of data compression: lossless and lossy.
Lossless compression ensures that no information is lost during the compression process, allowing for exact reconstruction of the original data. This is important for data that cannot be tolerated to lose any information, such as financial transactions. Lossy compression, on the other hand, sacrifices some information in order to achieve higher levels of compression. This is often used for data such as audio and video, where the loss of some information may not be noticeable to the human senses.
Lossless compression
One of the most widely used lossless compression algorithms is the Huffman coding algorithm. This algorithm assigns shorter codes to the more frequently occurring data items, resulting in more efficient storage and transmission.
Another popular lossless algorithm is the Lempel-Ziv-Welch (LZW) algorithm, which uses a dictionary-based approach to identify and compress repeated data patterns.
Please watch this youtube video to see how to implement in JavaScript an easy lossless compression / decompression algorithm.
Lossy compression
Lossy compression algorithms, on the other hand, often use mathematical transformations to represent the data in a more compact form. For example, the Discrete Cosine Transform (DCT) is commonly used in image and audio compression to represent the data in the frequency domain, where the most significant information can be preserved while discarding less important data.
In addition to these algorithms, there are also several general-purpose compression formats that can be used for different types of data. The most well-known of these is the ZIP format, which is commonly used to compress files for efficient storage and transmission.
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