Big Data Visualization: Bring scalability and dynamics to your Big Data visualization

Dalong Chen · James D. Miller

Feb 2017 · Packt Publishing Ltd

Ebook

304

Pages

Tools

About this ebook

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualizationKey Features

This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease
It is rich with ample options and solid use cases for big data visualization, and is a must-have book for your shelf
Improve your decision-making by visualizing your big data the right way

Book DescriptionGain 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 analyticsWhat you will learn

Get to grips with the basics of big data visualization before moving onto data storage, adding context to data using R, and addressing data quality issues. Learn how to use D3 and dashboards to display and present results, and how to use Python to deal with anomalies.

Who this book is for

Who is this book for? ? Data analysis beginners & data analysts who want to use visualization for more powerful analysis ? Knowledge of big data platform tools such as Hadoop & programming languages such as R is required

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualizationKey Features This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease It is rich with ample options and solid use cases for big...

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About the author

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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