What is data visualization? Purpose, types and importance

Data visualization is the presentation of data in a graphical format, making it easier to understand and interpret. It helps businesses make better decisions by quickly identifying patterns, trends, and anomalies in large datasets. The advantages of data visualization include improved comprehension, identification of patterns and trends, effective communication of insights, decision-making support, and enhanced collaboration and stakeholder engagement. Data visualization is important as it enables companies to generate ideas, illustrate concepts, and discover new information within complex datasets. It also helps teams work together by providing a shared way of looking at data, making it easier for them to understand and discuss the information. Common types of data visualizations include charts and graphs, infographics, maps and geographic visualization, network visualization, dashboards, and interactive data visualizations. Data visualization is crucial in real-time analytics as it allows users to monitor and respond to real-time data promptly. It enables organizations to observe and track data, provide immediate feedback on trends, patterns, and anomalies, and make timely decisions based on the insights gained from the data. Examples of data visualization use cases include sales and marketing, politics, healthcare, science, finance, logistics, and research. Data visualization best practices involve simplifying and focusing on crucial insights, using appropriate visual representations, ensuring data accuracy and integrity, providing context and relevance, and designing for user experience. Examples of data visualization tools include JupyterR, ChartBlocks, D3.js, FusionCharts, Grafana, Dundas BI, Power BI, Infogram, Google Charts, and Tableau. DoubleCloud is a platform that helps companies store and process large amounts of data efficiently, providing a solid foundation for creating meaningful and compelling visualizations.