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Home » Computer » Kindle Free Now You See It: Simple Visualization Techniques for Quantitative Analysis

Kindle Free Now You See It: Simple Visualization Techniques for Quantitative Analysis

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Computer
Thursday, November 28, 2013

Now You See It: Simple Visualization Techniques for Quantitative Analysis

Author: STEPHEN FEW | Language: English | ISBN: B0053T20VA | Format: EPUB

Now You See It: Simple Visualization Techniques for Quantitative Analysis Description

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  • ASIN: B0053T20VA
"Now You See It" is the latest book by author Stephen Few. The description says this book is a companion to "Show Me The Numbers," which is a favorite book of mine. "Show Me The Numbers" is about building charts and tables that will help you show others what you see in your data. "Now You See It" is about helping you to find new ways to display your data for your own analysis. Before you can show others your data you need to understand it yourself, and that's where this book fits in.

Creating charts is front and center as the focus of this book. "Show Me The Numbers" focused on charts and tables that could be built with simple tools such as Excel. Now You See It shows you the types of analysis you can do when you employee more advanced software such as Tableau and R. Some of the illustrations are really cool to look at and inspirational, even if I will never have the tools or time to prepare my own version of them.

"Now You See It" is broken up into 3 sections:

In Part 1 - Building Core Skills for Visual Analysis. Stephen Few covers the history of information visualization, the basics of analysis, and how we perceive data. There is some overlap with "Show Me The Numbers," but it's only one chapter, and not a deal breaker for me. I found the history of information visualization chapter interesting, and I imagine that in 50-100 years there are going to be new kinds of visualization methods available that we haven't even thought of yet.

In chapter 4, Analytical Interaction and Navigation, the author covers the role of good software in the data analysis process. He lists a few requirements that good software should have, and in many cases popular software such as Excel fall short.

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