Shannon's source coding theorem

Shannon's source coding theorem states that the most efficient way to compress data without losing any information is limited by the data's inherent uncertainty or randomness. It quantifies this limit with the entropy, which measures the average information content per symbol. Essentially, you cannot reliably compress data below its entropy rate without losing some details. This theorem guides how we develop data compression algorithms, ensuring we use storage and bandwidth efficiently while preserving the original information.