Metabolomics has emerged as a powerful discipline for characterizing the small molecules that define cellular physiology, environmental responses, and disease states. As technologies advance, researchers face an expanding landscape of analytical platforms, data-processing strategies, and integrative approaches that require clear guidance for effective application. This chapter was written to provide a comprehensive and accessible resource for students, clinicians, and researchers entering or advancing in the field. We outline the fundamentals of metabolomics, describe major analytical methodologies—including MS, NMR, chromatography, and imaging—and summarize key considerations for experimental design, data preprocessing, statistical analysis, and functional interpretation. We also address current challenges related to metabolite identification, reproducibility, and multi-omic integration, and highlight emerging innovations such as stable-isotope tracing, spatial metabolomics, and AI-driven analytics. Together, these elements offer a detailed roadmap for conducting robust, reproducible, and insightful metabolomic studies.