Aiming at the difficulty in elucidating the anti-tumor mechanism of Carthami Flos arising from its multi component and multi-target characteristics, big data technology was adopted to break through the research bottlenecks in the complex system of traditional Chinese medicine (TCM). Multi-omics and network pharmacology were integrated to construct a correlation database of Carthami Flos components and tumor targets. Combined with molecular docking, machine learning, and GO/KEGG enrichment analysis, a regulatory network of “component-target-pathway” was mapped. It was confirmed that the main active components of Carthami Flos include safflower yellow pigments and f lavonoids, which exert significant inhibitory effects on liver cancer, lung cancer and breast cancer. These components target AKT1, TP53 and other molecules, regulate the PI3K/Akt and MAPK signaling pathways, and exert their anti-tumor effects by inhibiting cell proliferation, promoting apoptosis, blocking the cell cycle and suppressing metastasis. Big data enables a panoramic elucidation of the anti-tumor mechanism of Carthami Flos, providing a new paradigm for the modernization of TCM and the research and development of new TCM preparations.