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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

View More author details

Table of Contents (9) Chapters

Preface

1. Introduction to Big Data Visualization

2. Access, Speed, and Storage with Hadoop FREE CHAPTER

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

About Tableau

A little background around Tableau. Tableau is not free although there are versions free to use (there is a difference) and there is a free use period, after which you must pay for the software.

Tableau offers five main products:

Tableau Desktop
Tableau Server
Tableau Online
Tableau Reader
Tableau Public

Tableau Public and Tableau Reader are free to use, while both Tableau Server and Tableau Desktop come with a 14-day fully functional free trial period.

Tableau is also not considered to be open source (as R and D3 are, for example), but Tableau is designed to support how you think, utilizing drag and drop to create visualizations of your data and leverage your natural ability to spot visual patterns quickly.

The foundation of Tableau combines a Structured Query Language (SQL) for databases with a descriptive language for rendering graphics, to invent a database visualization language called Visual Query Language (VizQL), making Tableau a unique tool for creating data visualizations...

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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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