Big Data Visualization

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization
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Big Data Visualization

James D. Miller

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization
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Book Details

ISBN 139781785281945
Paperback304 pages

Book Description

When it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations.

This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore "big data oriented" tools such as Hadoop and Tableau. We will show you how data changes with different variables and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics.

The choice of visualizations depends on the most suited techniques for big data, and we will show you the various options for big data visualizations based upon industry-proven techniques. You will then learn how to integrate popular visualization tools with graphing databases to see how huge amounts of certain data. Finally, you will find out how to display the integration of visual big data with BI using Cognos BI.

 

Table of Contents

Chapter 1: Introduction to Big Data Visualization
An explanation of data visualization
Challenges of big data visualization
Approaches to big data visualization
Summary
Chapter 2: Access, Speed, and Storage with Hadoop
About Hadoop
Log files and Excel
Hadoop and big data
Example 1
Example 2
Summary
Chapter 3: Understanding Your Data Using R
Definitions and explanations
Adding context
About R
Example 1
Digging in with R
Example 2
Summary
Chapter 4: Addressing Big Data Quality
Data quality categorized
DataManager
DataManager and big data
Some examples
More examples
Summary
Chapter 5: Displaying Results Using D3
About D3
D3 and big data
Some basic examples
More examples
Summary
Chapter 6: Dashboards for Big Data - Tableau
About Tableau
Tableau and big data
Example 1 - Sales transactions
Example 2
Summary
Chapter 7: Dealing with Outliers Using Python
About Python
Python and big data
Outliers
Some basic examples
More examples
Summary
Chapter 8: Big Data Operational Intelligence with Splunk
About Splunk
Splunk visualization -  real-time log analysis
Splunk visualization - deeper into the logs
Summary

What You Will Learn

  • Understand how basic analytics is affected by big data
  • Deep dive into effective and efficient ways of visualizing big data
  • Get to know various approaches (using various technologies) to address the challenges of visualizing big data
  • Comprehend the concepts and models used to visualize big data
  • Know how to visualize big data in real time and for different use cases
  • Understand how to integrate popular dashboard visualization tools such as Splunk and Tableau
  • Get to know the value and process of integrating visual big data with BI tools such as Tableau
  • Make sense of the visualization options for big data, based upon the best suited visualization techniques for big data

Authors

Table of Contents

Chapter 1: Introduction to Big Data Visualization
An explanation of data visualization
Challenges of big data visualization
Approaches to big data visualization
Summary
Chapter 2: Access, Speed, and Storage with Hadoop
About Hadoop
Log files and Excel
Hadoop and big data
Example 1
Example 2
Summary
Chapter 3: Understanding Your Data Using R
Definitions and explanations
Adding context
About R
Example 1
Digging in with R
Example 2
Summary
Chapter 4: Addressing Big Data Quality
Data quality categorized
DataManager
DataManager and big data
Some examples
More examples
Summary
Chapter 5: Displaying Results Using D3
About D3
D3 and big data
Some basic examples
More examples
Summary
Chapter 6: Dashboards for Big Data - Tableau
About Tableau
Tableau and big data
Example 1 - Sales transactions
Example 2
Summary
Chapter 7: Dealing with Outliers Using Python
About Python
Python and big data
Outliers
Some basic examples
More examples
Summary
Chapter 8: Big Data Operational Intelligence with Splunk
About Splunk
Splunk visualization -  real-time log analysis
Splunk visualization - deeper into the logs
Summary

Book Details

ISBN 139781785281945
Paperback304 pages
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