Visualization

The main point (although there are other goals and objectives) when leveraging a data visualization technique is to make something complex appear simple. You can think of visualization as any technique for creating a graphic (or similar) to communicate a message.

Other motives for using data visualization include the following:

• To explain the data or put the data in context (which is to highlight demographical statistics)
• To solve a specific problem (for example, identifying problem areas within a particular business model)
• To explore the data to reach a better understanding or add clarity (such as what periods of time do this data span?)
• To highlight or illustrate otherwise invisible data (such as isolating outliers residing in the data)
• To predict, such as potential sales volumes (perhaps based upon seasonality sales statistics)
• And others

Statistical visualization is used in almost every step in the data science process, within the obvious steps such as exploring and visualizing, analyzing and learning, but can also be leveraged during collecting, processing, and the end game of using the identified insights.