Book Image

Big Data Visualization

Book Image

Big Data Visualization

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

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Table of Contents (15 chapters)
Big Data Visualization
Big Data Visualization
Credits
Credits
About the Author
About the Author
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Introduction to Big Data Visualization
Introduction to Big Data Visualization
An explanation of data visualization
Challenges of big data visualization
Approaches to big data visualization
Summary
2
Access, Speed, and Storage with Hadoop
Access, Speed, and Storage with Hadoop
About Hadoop
Log files and Excel
Hadoop and big data
Example 1
Example 2
Summary
3
Understanding Your Data Using R
Understanding Your Data Using R
Definitions and explanations
Adding context
About R
Example 1
Digging in with R
Example 2
Summary
4
Addressing Big Data Quality
Addressing Big Data Quality
Data quality categorized
DataManager
DataManager and big data
Some examples
More examples
Summary
5
Displaying Results Using D3
Displaying Results Using D3
About D3
D3 and big data
Some basic examples
More examples
Summary
6
Dashboards for Big Data - Tableau
Dashboards for Big Data - Tableau
About Tableau
Tableau and big data
Example 1 - Sales transactions
Example 2
Summary
7
Dealing with Outliers Using Python
Dealing with Outliers Using Python
About Python
Python and big data
Outliers
Some basic examples
More examples
Summary
8
Big Data Operational Intelligence with Splunk
Big Data Operational Intelligence with Splunk
About Splunk
Splunk visualization -  real-time log analysis
Splunk visualization - deeper into the logs
Summary

Summary

In this chapter, we covered some basic data quality concepts and introduced various categories for data quality. In addition, the easily obtainable and extremely useable DataManager tool was presented as a means for addressing these various data quality issues.

In the next chapter, we will get back to the business of data visualization and some of the challenges big data brings to visualization, using D3 to effectively present the results from analyses.

Previous Section
End of Chapter 4
Next Chapter