This chapter covers digital information sources in some depth. It provides intuition on the information content of a digital source and introduces the notion of redundancy. As a simple but important example, discrete memoryless sources are described. The concept of entropy is defined as a measure of the information content of a digital information source. The properties of entropy are studied, and the source-coding theorem for a discrete memoryless source is given. In the second part of the chapter, practical data compression algorithms are studied. Specifically, Huffman coding, which is an optimal data-compression algorithm when the source statistics are known, and Lempel–Ziv (LZ) and Lempel–Ziv–Welch (LZW) coding schemes, which are universal compression algorithms (not requiring the source statistics), are detailed.