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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 D3

D3 (or D3.js) is actually an open source JavaScript library (based upon its predecessor, the Protovis framework), designed with the intention of visualizing data using todays web standards.

D3 helps put life into your data utilizing Scalable Vector Graphics (SVG), Canvas, and standard HTML.

D3 combines powerful visualization and interaction techniques with a data-driven approach to DOM manipulation, giving you the full capabilities of modern browsers and the freedom to design the right visual interface for your data.

In contrast to many other libraries, D3.js allows inordinate control over the visualization of your data. Its development was noted in 2011, as version 2.0.0 was released in August 2011.

D3 is embedded within an HTML webpage, and uses prebuilt JavaScript functions to select elements, create SVG objects, style them, or add transitions, dynamic effects, and so on.

Detailed information, including the D3.js libraries can be accessed at https://D3js.org.

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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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