The book 'Signal' by Stephen Few is praised for its accessible approach to data visualization, blending insights from Tufte and Wheeler. It emphasizes the importance of extracting meaningful information from data amidst increasing noise, offering practical tools and techniques for effective data analysis and visualization.
The reviewer highlights 'Signal' as a valuable resource for anyone working with data, noting its accessible style and beautiful design, reminiscent of Tufte's work. The book effectively combines principles from Tufte and Wheeler, focusing on the crucial task of extracting signals from noise in an era of big data. Few's background in business intelligence and information design brings a unique perspective, making the book suitable for both beginners and experienced professionals. The first three-quarters of the book cover foundational graphical tools for assessing variation, while the latter part discusses combining these tools for deeper insights. Despite minor critiques, such as the brevity of the dashboard design chapter, the book is highly recommended for its practical advice on data visualization.
Quick quotes
People are already struggling to use data effectively and having a harder time as the volume of data grows. As we turn up the volume of noise, it becomes increasingly difficult to hear anything meaningful. It’s like a radio that’s stuck on static between channels at maximum volume. If only we could turn the dial to find a clear channel. Finding a needle in a haystack doesn’t get easier as we’re tossing more and more hay on the pile. (p. 3)
Take Tufte (2001) and smash it together with Wheeler (2000) and you have this book written by Stephen Few, who has a background is in business intelligence and information design.
Ultimately, I’m looking forward to reading more of Few’s books.