Data visualization is the representation of data in a visual format such as graphs, charts, and other visual aids. Data visualization assets are found in dashboards, reports, or notebooks. They are usually set up by the data team which choses the best representation of their analysis.
Data visualization allows users to see patterns, trends, and relationships that may not be apparent in raw data. By using visual aids to represent complex data, users can quickly identify key insights and take action.
In today's fast-paced business environment, decision-makers need quick and easy access to relevant data to make informed decisions. Data visualization provides an efficient way to convey information to users, regardless of their technical expertise. Visual representations of data enable business users to quickly identify trends and patterns, identify outliers, and make informed decisions.
There are many types of data visualization, including line charts, bar charts, pie charts, scatter plots, and heat maps. Each type of visualization is best suited for specific types of data, and it is essential to choose the right one to ensure the most effective communication of information. For example, funnel charts are excellent for visualizing a sequential process or a series of steps with different stages or levels, such as measuring a conversion rate - as pictured under.
Effective data visualization requires careful planning and execution. Here are some best practices to follow when creating visualizations: