A Comparative Analysis of Data Compression Techniques

Data compression is the process that is used to reduce the physical size of a block of information; data compression encodes information using fewer bits to help in reducing the consumption of expensive resources such as disk space or transmission bandwidth. The task of compression consist of two components, an encoding algorithm that takes a message and generates a compressed representation (hopefully with fewer bits), and a decoding algorithm that reconstructs the original message or some approximation of it from the compressed representation. Data Compression is divided into two (2) broad categories namely Lossless compression and lossy algorithms. This paper examined these compression techniques and provided a comparative analysis of three commonly used compression techniques (the Huffman, Lempel-Ziv and RunLength Encoding). The results revealed that compression algorithms can be proven to be more effective on notepad, text, web documents, PDF, Images and sound.