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Big Data Visualization

You're reading from Big Data Visualization Bring scalability and dynamics to your Big Data visualization

Product type Paperback

Published in Feb 2017

Publisher Packt

ISBN-13 9781785281945

Length 304 pages

Edition 1st Edition

Languages

R

Tools

D3

Concepts

Big Data

Author (1):

James D. Miller

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Table of Contents (15) Chapters

Big Data Visualization

Credits

About the Author

About the Reviewer

www.PacktPub.com

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Preface

1. Introduction to Big Data Visualization FREE CHAPTER

2. Access, Speed, and Storage with Hadoop

3. Understanding Your Data Using R

4. Addressing Big Data Quality

5. Displaying Results Using D3

6. Dashboards for Big Data - Tableau

7. Dealing with Outliers Using Python

8. Big Data Operational Intelligence with Splunk

Chapter 6. Dashboards for Big Data - Tableau

If a picture is worth a thousand words then a dashboard is worth millions.

Visual dashboards that effectively present the results of multiple analysis--sometimes in real time--are invaluable to businesses of all kinds.

In this chapter, we introduce Tableau as a data visualization tool that can be used to construct dashboards, providing working examples demonstrating solutions for effectively presenting results from your big data analysis in a real-time dashboard format.

This chapter is organized into the following main sections:

About Tableau
Tableau and big data
Example 1
Example 2

The rest of the chapter is locked

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Authors (1)

James D. Miller

James D. Miller

James D. Miller is an IBM certified expert, Master Consultant, Application/System Architect with +35 years of applications & system design/development experience across multiple platforms, technologies and data formats, including Big Data. His experience includes IBM Planning Analytics, BI, Web architecture & design, systems analysis, GUI design & testing, Data modeling, design, and development of OLAP, Client/Server, Web & Mainframe applications and systems utilizing: Planning Analytics Workspace (PAW), IBM Watson Analytics, Cognos BI & TM1, Framework Manager, dynaSight/ArcPlan, ASP, DHTML, XML, MS Visual Basic, VBA, PERL, R, SPLUNK, MS SQL Server, ORACLE, etc. He has authored numerous books, including Implementing Splunk - Second Edition; Mastering Splunk; Hands-On Machine Learning with IBM Watson; IBM Watson Projects; Statistics for Data Science; Mastering Predictive Analytics with R - Second Edition and others. Project areas include those with Data Analytics, Planning Analytics, and FOPM projects, holding various roles from architect, developer, technical and project leader.

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