Big Data Visualization

by James D. Miller

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization About This Book 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 Who This Book Is For This book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations. What You Will Learn Understand how basic analytics is affected by big data Deep dive into effective and efficient ways of visualizing big data Get to know various approaches (using various technologies) to address the challenges of visualizing big data Comprehend the concepts and models used to visualize big data Know how to visualize big data in real time and for different use cases Understand how to integrate popular dashboard visualization tools such as Splunk and Tableau Get to know the value and process of integrating visual big data with BI tools such as Tableau Make sense of the visualization options for big data, based upon the best suited visualization techniques for big data In Detail When it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations. This book works around big data visualizations and the challenges around visualizing big data and address

304 pages, Paperback

Published February 28, 2017

Reviews

[Kevin Narvaes · Rating 4 out of 5]

The book provides really good insights on some of the most popular tools for data science, addressing issues like dealing with outliers, preprocessing data, showing your data in meaninful and easy to understand ways, dealing with different scenarios presented in real world problems demanding knowing skills in the usage of data.

There were a few typos here and there, and I consider a few more detail could had went in some of the examples.

Other than that, it's an eady to read pick for anyone knowing some basic data science stuff and trying to learn about the different situations one might have to confront.