trat 1

• Data visualization is the visual representation and presentation of data to facilitate understanding.
• Data consists of amounts and names, mostly text, numbers, or both.
• Data assets can be in media forms such as images, audio, and video.
• Without visualization, the value of data can be unfulfilled.
• It is difficult to make broad observations of data without proper visualization.
• Visual representation is the quintessential activity of data visualization.
• Decisions on how to portray data visually should be made to make it understandable for end users.
• The right chart should be selected to show the features of data that are most relevant.
• Building blocks of charts include marks, which are points, lines, or shapes used to represent items of data.
• Marks represent the thing the value is about, not the value itself.
• Attributes (channels) are visual variations of marks to represent values associated with each.
• Consuming data in chart forms allows users to process clusters of multiple data points simultaneously, such as slopes and gaps.
• Making observations of collective patterns becomes more precise with charting data.
• Charting data helps to see different features of the data rather than using a table.
• Presentation in data visualization concerns all other design decisions that make up the full anatomy of any visualization.
• Design decisions in presentation include design choices, annotation, title, color legend, x and y axis scales, interactivity, color usage, and composition of work.
• Small design decisions in visualization make a big impact.
• Divide design concerns into separate layers in data visualization.
• Three Phases of Understanding in data visualization are perceiving, interpreting, and comprehending.