Book SummaryThe Big Book of Dashboards, by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave

1-Page Summary1-Page Book Summary of The Big Book of Dashboards

Fundamental guidelines for creating interfaces and designs for data visualizations and dashboards.

Explore the core concepts and techniques necessary to create dashboards that are not just functional but also highly influential.

Delve into how preattentive attributes can be utilized to create visuals that effectively and engagingly communicate information.

The book begins by exploring how our brains swiftly interpret visual data, introducing a concept known as "preattentive attributes." Our instinctive perception identifies characteristics such as color, size, shape, and spatial placement before our conscious mind begins to process the visual data. By thoughtfully incorporating these elements into your visualizations, you can ensure that the most important data points capture the viewer's attention.

A red dot stands out prominently in a sea of gray ones. Your mind subconsciously discerns the variation in hue before you consciously register the numerous surrounding dots of a muted shade. Think about utilizing a bar graph. We instinctively evaluate the length of the bars rather than relying on numerical computations to identify which is the longest or shortest. Our understanding is subtly shaped by specific factors that capture our attention, especially the notion of time span within this context. The authors highlight the importance of employing visual cues such as size and placement to effectively assess numerical information, which is crucial for identifying top-selling items or the most profitable regions.

Investigate the different types of data, including categorical, ordinal, and quantitative, to determine the most suitable visual representations for them.

Choosing a suitable chart necessitates a deep understanding of the information available. Initially, it's essential to ascertain the nature of your data, determining if it is qualitative, ranked, or numerical in nature. Categorical data, which encompasses classifications like product types, city names, or gender distinctions, serves the purpose of labeling without possessing numerical significance. The text explores a range of subjects, one of which is the widely recognized Net Promoter Score, an indicator of customer allegiance. Finally, quantitative data comprises numerical values that we gather and examine to identify trends, including sales, profit, student performance ratings, or the number of patients admitted to hospitals.

Upon identifying the nature of your data, you can convert it into a visual form by selecting the appropriate preattentive attribute. To demonstrate the differences in sales volume across different regions, bars of varying lengths represent the sales totals for each region. Each categorical variable would correspond to a specific geographic area. To accurately portray how various ages are spread out in a group, choose a histogram with a numerical axis for age representation and with bars that indicate the quantity of people in each age range through their height.

Explore various graph styles and determine the appropriate occasions for their application to enhance comprehension.

The book highlights a range of essential and commonly utilized visual tools, such as the steadfast column graph, time-series graphs, and diagrams that reveal relationships, in addition to geographically enhanced maps like choropleth and symbol maps, flexible grid displays, bullet graphs for juxtaposing real results with goals, and the informative highlight table. When selecting a chart type, it's essential to...