Packt+ | Advance your knowledge in tech

0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

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 Hadoop

Let's start out with an explanation of Hadoop that is generally circulated.

As per Apache Hadoop wikipedia.org, 2016:

"Hadoop is an open-source software "framework" for distributed storage and distributed processing (of very large datasets) on computer clusters built from commodity hardware."

The following is a visualization that may help understand the master-to-slave architecture used by Hadoop:

Hadoop uses an architecture called MapReduce. This is a design that designates a processor (in a cluster of processors) as the master, which controls distributing or mapping tasks to other slave processors to process your data, thus reducing the processing performed by the cluster of processors to a single output result. So, you can now see that the name mapped reduction or MapReduce (of processing tasks) makes sense.

Hadoop is able to take your data and split it up (or distribute it) over a number of computers that have space or resources available.

These computers need not be high...

You have been reading a chapter from

Big Data Visualization

Published in: Feb 2017

Publisher: Packt

ISBN-13: 9781785281945

© 2017 Packt Publishing Limited All Rights Reserved

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at €18.99/month. Cancel anytime

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.

See other products by James D. Miller

Other recommended products

Related to this chapter

Statistics for Data Science

Statistics for Data Science

Statistics is an absolute must prerequisite for any task in the area of data science. This is also the most feared hindrance for developers to entering in the data science field. This book will start off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for the statistical computations will be clearly explained along with the logic. You will come across various mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis.

Nov 2017 9h 32m

Statistics for Data Science

Statistics for Data Science

Statistics is an absolute must prerequisite for any task in the area of data science. This is also the most feared hindrance for developers to entering in the data science field. This book will start off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for the statistical computations will be clearly explained along with the logic. You will come across various mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis.

Nov 2017 9h 32m

Statistics for Data Science

Statistics for Data Science

Statistics is an absolute must prerequisite for any task in the area of data science. This is also the most feared hindrance for developers to entering in the data science field. This book will start off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for the statistical computations will be clearly explained along with the logic. You will come across various mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis.

Nov 2017 9h 32m

Statistics for Data Science

Statistics for Data Science

Statistics is an absolute must prerequisite for any task in the area of data science. This is also the most feared hindrance for developers to entering in the data science field. This book will start off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for the statistical computations will be clearly explained along with the logic. You will come across various mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis.

Nov 2017 9h 32m

Statistics for Data Science

Statistics for Data Science

Statistics is an absolute must prerequisite for any task in the area of data science. This is also the most feared hindrance for developers to entering in the data science field. This book will start off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for the statistical computations will be clearly explained along with the logic. You will come across various mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis.

Nov 2017 9h 32m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Splunk 7 Essentials

Splunk 7 Essentials

This book will uncover the new features in Splunk 7 along with the best practices. You will learn to build navigable search operations, perform intuitive statistical analysis and design visually appealing dashboards for your IT infrastructure. With practical scenarios, you'll be able to design cohesive Splunk apps and deploy it to Splunk cloud.

Mar 2018 7h 20m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.