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Introduction to R for Business Intelligence

You're reading from   Introduction to R for Business Intelligence Profit optimization using data mining, data analysis, and Business Intelligence

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Product type Paperback
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Length 228 pages
Edition 1st Edition
Languages
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Author (1):
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Jay Gendron Jay Gendron
Author Profile Icon Jay Gendron
Jay Gendron
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Table of Contents (13) Chapters Close

Preface 1. Extract, Transform, and Load FREE CHAPTER 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny A. References
B. Other Helpful R Functions C. R Packages Used in the Book
D. R Code for Supporting Market Segment Business Case Calculations

Visualizing data


Your journey into the world of visualization starts with this observation-numbers are explicit and objective, visuals are implicit and subjective. Hidden within the numbers, shapes, and colors is a message that is subject to the interpretation of the viewer. Realize what happens as the visual image transforms through our senses into an understanding. The brain will subconsciously pass judgement in determining what information is essential and what is supportive. Sight becomes perception. Perception becomes cognition and knowledge (Cairo, 2013).

Calling attention to information

If sight is perception, then data storytellers must consider how to use visual elements to call attention to the most critical information. According to Cairo (2013), The brain is much better at quickly detecting shade variations than shape differences (p. 113). He provides tips on how to call the user's attention to particular portions of a visual. First, he suggests using pure colors to highlight the...

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