This project implements a dual-algorithm lossless data compression system using Huffman Coding and Shannon-Fano algorithms to optimize digital storage and transmission. Developed using Python and C++, the system compresses and decompresses files by generating binary encoding trees based on character frequency while preserving complete data integrity. The project demonstrates efficient file size reduction, with Huffman Coding achieving better compression rates and Shannon-Fano providing simpler and faster processing for smaller datasets. The solution can be applied in storage systems, network transmission, and archival management to improve digital resource efficiency.