Visual Analytics - An Interaction of Sight and Thought - JMP

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Good analysis tools augment memory by expanding... • Quantity • Dimensions • Perspectives Good visual analysis software can help us overcome the limitations of working memory in several ways. The goal is to enable as many meaningful comparisons as possible. Good tools can help us increase: • The amount of information that we can compare (that is, greater quantity) • The range of information that we can compare (that is, more dimensions) • The different views of the information that we can compare (that is, multiple perspectives)
Greater quantity through visual encoding 1 chunk Traditional BI relies mostly on tabular data displays. Tables are wonderful if you need to look up individual values, compare a single value to another, or know values precisely, but they don’t display patterns or trends. This is a problem, because data analysis relies heavily on our ability to spot and make sense of patterns and trends in data. Take a look at the table and compare it to this line graph, which displays the same data. Relying on the table to discern the ups and downs of sales through time and to compare the patterns of change from region to region would yield very little of the information that is obvious in this graph. Visual representations give form to data, making pattern, trends, and exceptions easy to see. Another advantage of properly designed graphs over tables for analytical purposes is less obvious. If you needed to remember information in the table, you could hold only about four of the values (that is, four of the monthly sales numbers) in working memory at any one time. But by relying on the graph, 12 values are combined into each of the four lines to form a pattern that you could hold entirely as a single chunk in working memory. Simply by giving visual form to the values, you can hold much more information in memory.
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Visual Analytics An Interaction of
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Hurray data! Hurray technology! We
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Upon this gifted age, in its dark h
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We must tap into that steady stream
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Data analysts JMP are now sexy. Dat
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To do this we need the right skills
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Two of the right skills • Statist
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What is visual thinking? Temple Gra
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We need greater balance. Modes of r
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Leonardo da Vinci For some four hun
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Complex problems require visual thi
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Tools extend our reach when they’
Page 26 and 27: Can computers replace us? Our brain
Page 28 and 29: Visualization empowers statistics.
Page 30 and 31: “I see!” There is an intimate c
Page 32 and 33: Vision is our dominant sense. 30% 7
Page 34 and 35: Trends, patterns, and exceptions co
Page 36 and 37: This visualization fails to do this
Page 38 and 39: The right balance 38 Information vi
Page 40 and 41: Many visualization tools feature de
Page 42 and 43: Bling your graph. Many software ven
Page 44 and 45: 3-D graphs are rarely useful. One o
Page 46 and 47: Even when there’s a 3 rd variable
Page 48 and 49: We don’t want to confuse people w
Page 50 and 51: Good visualizations and good visual
Page 52 and 53: This arrangement is even better yet
Page 54 and 55: Visual perception works according t
Page 56 and 57: Visual perception is not just camer
Page 58 and 59: Two essential activities • Multi-
Page 60 and 61: Data analysis requires rapid intera
Page 62 and 63: Key interactions of visual analysis
Page 64 and 65: Shneiderman’s Mantra “Overview
Page 66 and 67: Overview first, zoom and filter, th
Page 72 and 73: Attention is limited. Ever saw a ma
Page 74 and 75: Capacity = 3 or 4 chunks at a time
Page 78 and 79: More dimensions through multiple vi
Page 80 and 81: Coordinated views expand what we ca
Page 82 and 83: Analytical challenges demand statis
Page 84 and 85: Predictions rely on statistical mod
Page 86 and 87: Finding and understanding the stori
Page 88 and 89: Wisdom Knowledge Information Inform
Page 90 and 91: O perpetual revolution of configure
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Visual Analytics - An Interaction of Sight and Thought - JMP

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