ABSTRACT
This chapter addresses the questions of critical and deserve empirical investigation by providing a review of good data visualization practice techniques as articulated by the leading scholars and practitioners. It discusses leading data visualization components to ensure data visualizations are used effectively. The chapter provides the data visualization, there are still clearly defined metrics or evaluation methods to measure effectiveness for tools and systems. It also provides two broad types of visualizations: multidimensional visualization and hierarchical and landscape visualization. Visualization fosters the constructive evaluation, correction, and ultimately, the improvement of the management of knowledge on all levels, including personal, interpersonal, team, organizational, inter-organizational, and societal, as well as enhancement of decision-making process and management capabilities. As the field of data analytics and visualization has matured, the principle of data visualization has evolved from a single universe set into a more complex, but still loosely defined structure. In data visualization, color should not be used for decorative or non-informational purposes.
