Big Data Visualization transforms massive, complex datasets into understandable, actionable insights through graphical representation. It combines statistical analysis, machine learning, and interactive dashboards to reveal patterns, trends, and anomalies in structured, unstructured, and streaming data. Tools like Tableau, Power BI, Python libraries (Matplotlib, Seaborn, Plotly), R, Grafana, and Folium support time-series, geospatial, network, and multidimensional visualization. Techniques include line charts, scatter plots, heatmaps, 3D surfaces, and word clouds, enabling both exploration and decision-making. Visualization improves comprehension, aids predictive modeling, and facilitates communication of insights across stakeholders. It is essential in research, enterprise analytics, IoT, healthcare, finance, and smart systems.