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Data visualization is the graphical translation and representation of information into a visual context. Using techniques such as charts, graphs and maps, it enables visual communication and exploration of qualitative and quantitative data by highlighting key changes, patterns and trends that make it easier for people to identify relevant insights and make informed decisions.
As a core business intelligence and data analytics capability today, data visualization is typically used to measure business performance and provide a visual overview of large data-sets that can be more efficiently analyzed than data in its raw form. Examples of visualizations include bar, flow, line and pie charts, heat and tree maps, histograms, infographics and scatter plots.
Data visualization improves the accessibility and value of data within a business by allowing non-statistically trained users to rapidly gain insights about key decisions, and enhances the analysis of experienced data analysts and scientists by visualizing complex metrics or numerical outputs into quick and efficient visual information. When used correctly, it effectively transforms organizational data into easily digestible and actionable business communications for everyone.
The rise and prevalence of big data today has made data visualization more important than before, as the sheer volume of incoming data requires a way to sort through complex information and cleanly present the most critical areas for stakeholders to glean insights fast. To better understand why you need data visualization, watch our webinar to learn how to choose, design and deliver the best visualizations to effectively communicate the significance of your metrics and trends.
Data visualization capabilities differs from platform to platform. To see the rich data storytelling and visualization features of Yellowfin BI for yourself, we recommend visiting our interactive dashboard gallery.