Handbook of Research on Big Data Storage and Visualization Techniques Front Cover

Handbook of Research on Big Data Storage and Visualization Techniques

  • Length: 917 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2018-01-05
  • ISBN-10: 1522531424
  • ISBN-13: 9781522531425
  • Sales Rank: #21259934 (See Top 100 Books)
Description

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data.

The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

Table of Contents

Section 1: Introduction to Big Data and Storage Systems
Chapter 1: Overview of Big Data and Its Visualization
Chapter 2: Overview of Big-Data-Intensive Storage and Its Technologies

Section 2: Big Data Technologies and Architectural Patterns
Chapter 3: Database Systems for Big Data Storage and Retrieval
Chapter 4: Hadoop Framework for Handling Big Data Needs
Chapter 5: Role of Open Source Software in Big Data Storage

Section 3: Big Data in Clouds, Clusters, and Grids
Chapter 6: Big Data Tools for Computing on Clouds and Grids
Chapter 7: A Review of Security Challenges in Cloud Storage of Big Data
Chapter 8: Architecture for Big Data Storage in Different Cloud Deployment Models

Section 4: Big Data Processing for Storage and Visualization
Chapter 9: Programming and Pre-Processing Systems for Big Data Storage and Visualization
Chapter 10: High Performance Storage for Big Data Analytics and Visualization
Chapter 11: Big Data in Massive Parallel Processing
Chapter 12: Distributed Streaming Big Data Analytics for Internet of Things (IoT)

Section 5: Applications of Big Data Storage
Chapter 13: Scalable Data Warehouse Architecture
Chapter 14: Resource Provisioning and Scheduling of Big Data Processing Jobs
Chapter 15: Issues and Methods for Access, Storage, and Analysis of Data From Online Social Communities
Chapter 16: Big Data Storage for the Modeling of Historical Time Series Solar Irradiations

Section 6: Visualization Tools and Techniques
Chapter 17: Big Data Visualization Tools and Techniques
Chapter 18: The Image as Big Data Toolkit
Chapter 19: Statistical Visualization of Big Data Through Hadoop Streaming in RStudio
Chapter 20: Visualization of Big Data Sets Using Computer Graphics
Chapter 21: Visualization of Predictive Modeling for Big Data Using Various Approaches When There Are Rare Events at Differing Levels
Chapter 22: Introduction to Smart City and Agricultural Revolution
Chapter 23: Mining Multimodal Big Data

Section 7: Applications of Big Data Visualization
Chapter 24: Big Data and Its Role in Facilitating the Visualization of Financial Analytics
Chapter 25: Visualization and Storage of Big Data for Linguistic Applications
Chapter 26: Big Data Analysis Techniques for Visualization of Genomics in Medicinal Plants
Chapter 27: The Artist’s Move
Chapter 28: Visualizing Big Data From a Philosophical Perspective
Chapter 29: Big Data Analytics and Visualization of Performance of Stock Exchange Companies Based on Balanced Scorecard Indicators
Chapter 30: Visualization Tools for Big Data Analytics in Quantitative Chemical Analysis

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