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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
Free Chapter
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
4
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
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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

Log files and Excel

Let's consider a somewhat realistic use case where you have been provided a number of modified web log files that you want to create some visualizations from.

In Chapter 4, Addressing Big Data Quality, we will discuss data profiling (in regards to data quality), but for now, we'll assume that we know the following about our data files:

  • The files are of various sizes and somewhat unstructured.

  • The data in the files contain information logged by Internet users.

  • The data includes such things as computer IP addresses, a date, timestamp, and a web address/URL. There is more information in the files, but for our exercise here we really just want to create a graphical representation showing the number of times each web address was hit during each month (there are actually software packages that provide web statistics, but we'll suppose you don't have access to any of them).

The following is a sample transaction (record) from one of our files:

221.738.236 - - [15/Oct/2014:6:55:2] GET...

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