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  • Book Overview & Buying Big Data Visualization
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Big Data Visualization

Big Data Visualization

By : James D. Miller
2 (1)
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Big Data Visualization

Big Data Visualization

2 (1)
By: James D. Miller
Buy this Book

Overview of this book

Gain valuable insight into big data analytics with this book. Covering the tools you need to analyse data, together with IBM certified expert James Miller?s insight, this book is the key to data visualization success. ? Learn the tools & techniques to process big data for efficient data visualization ? Packed with insightful real-world use cases ? Addresses the difficulties faced by professionals in the field of big data analytics
Table of Contents (9 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction to Big Data Visualization
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1. Introduction to Big Data Visualization
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An explanation of data visualization
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Challenges of big data visualization
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Approaches to big data visualization
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Summary
2
2. Access, Speed, and Storage with Hadoop
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2. Access, Speed, and Storage with Hadoop
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About Hadoop
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Log files and Excel
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Hadoop and big data
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Example 1
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Example 2
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Summary
3
3. Understanding Your Data Using R
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3. Understanding Your Data Using R
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Definitions and explanations
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Adding context
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About R
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Example 1
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Digging in with R
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Example 2
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Summary
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4. Addressing Big Data Quality
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4. Addressing Big Data Quality
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Data quality categorized
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DataManager
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DataManager and big data
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Some examples
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More examples
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Summary
5
5. Displaying Results Using D3
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5. Displaying Results Using D3
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About D3
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D3 and big data
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Some basic examples
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More examples
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Summary
6
6. Dashboards for Big Data - Tableau
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6. Dashboards for Big Data - Tableau
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About Tableau
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Tableau and big data
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Example 1 - Sales transactions
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Example 2
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Summary
7
7. Dealing with Outliers Using Python
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7. Dealing with Outliers Using Python
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About Python
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Python and big data
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Outliers
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Some basic examples
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More examples
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Summary
8
8. Big Data Operational Intelligence with Splunk
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8. Big Data Operational Intelligence with Splunk
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About Splunk
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Splunk visualization -  real-time log analysis
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Splunk visualization - deeper into the logs
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Summary

Python and big data

Python is a very good choice for big data manipulations and, as we'll see in this chapter, for addressing big data outliers. This is due to the following points:

  • It's easy to understand and use. You can learn Python relatively quickly and get on to the true task at hand: manipulating and processing your big data.

  • Python comes with a wide range of prebuilt libraries focused on data processing, visualization, and other data manipulations. This saves, even more, Python is very versatile and powerful and has increased in popularity of thetime by providing solutions to the most fundamental tasks required to process big data.

  • Although Python is a general purpose language that runs just about anywhere, it is flexible and nimble enough to provide the ability to create very custom solutions to address unique problems associated with big data.

All the preceding features prove the point for using Python for manipulating and processing big data to generate quick insights valuable to...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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Big Data Visualization
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