The development of second-generation sequencing (NGS) technology is providing numerous data which shifts the focus of cancer research from the sequencing of multi-species to the analysis and comparison of select data via high-throughput sequencing. The NGS also facilitates the diversity of available genetic data analysis methods, the constant optimization and innovation of analytical approaches for high-throughput genomics as well as the rapid development of genetic data mining and analysis models. The Cancer Genome Atlas (TCGA) database is a direct result of this work. The TCGA database provides a comprehensive record of genetic data collected from a tumor patient's sample, including its DNA sequence, transcriptional information, epigenetic modification and related. This review elaborates the latest progress in both the mining algorithm and analysis methods for tumor genomics. Specially, we introduce and review the TCGA database and data analysis approaches while demonstrating its applicability using representative cases. This review may shed light on new tumor-related targets discovery for researchers by means of bid data.