Abstract - In spite in advances in technologies for working with data, people spend undue amount of time in understanding the data and manipulating it into holistic visualization. Data visualization software for complex dataset such as in cancer genomics (which we have taken as case study) are not able to provide effective visualization for the users. Identification and characterization of cancer detection are important areas of research that are based on the integrated analysis of multiple heterogeneous genomics datasets. In this report, we review the key issues and challenges associated with cancer genomics through exploration of data visualization techniques, interactions and methods, which will in-turn advance the state of the art.