Metabolomics and multi-omics (genomics, transcriptomics, and proteomics) offer a profound comprehension of biological systems. This integration provides a clear view of cellular functions and their interactions. The study of small molecules and investigating their biochemical activities within cells in a system is termed metabolomics. Combined with related omics data, this information enhanced understanding resolution through detailed analysis of biological processes, such as disease mechanisms and potential therapeutic targets. Herein, through this book chapter, we aim to explain advanced technologies in metabolomics, highlight their principles and methodologies involved to address challenges and opportunities in multi-omics integration, and present a case study on their application in health and disease research. Reviewing current literature on the application of mass spectrometry (MS), which identifies and quantifies metabolites, and nuclear magnetic resonance (NMR) spectroscopy, we further enhance our understanding of structural information about metabolites. The application of advanced bioinformatics tools for integrating and interpreting large-scale omics data and their linkage with metabolomics will also be discussed. These tools are crucial for handling the vast amount of data generated and extracting meaningful insights. To illustrate practical applications, we will also include various studies where integrated omics approaches have been successfully applied. We also comprehend how these tools can help improve diagnostic accuracy and develop targeted therapies and personalized medicine. The emerging trends in integrative omics research, the ongoing challenges, and potential solutions will also be discussed. To enhance the effectiveness of this approach, we will include detailed descriptions of figures and tables, such as workflow integration illustrations, metabolic pathways, and visual representations of multi-omics data integration. Taken together, this approach will provide researchers and practitioners with a thorough understanding of the current state and future potential of integrative omics technologies in biological analysis. The insights gained from this information will have significant implications for improving the existing information of the application of the tools to understand biological processes comprehensively.