Название: Data Visualization: Trends and Challenges Toward Multidisciplinary Perception
Автор: S. Margret Anouncia, Hardik A. Gohel
Издательство: Springer
Год: 2020
Страниц: 188
Язык: английский
Формат: pdf (true)
Размер: 11.4 MB

Represents data visualization in multidisciplinary percetion. Includes tips on how to protect flash sites from hackers.

This book discusses the recent trends and developments in the fields of information processing and information visualization. In view of the increasing amount of data, there is a need to develop visualization techniques to make that data easily understandable. Presenting such approaches from various disciplines, this book serves as a useful resource for graduates.

Visualization is one of the most important components of research presentation and communication due to its ability to synthesize large amounts of data into effective graphics. It is easier for the brain to comprehend an image versus words or numbers making effective graphics an especially important part of academic literature. The increasing accessibility and quantity of data require effective ways to analyze and communicate the information that datasets contain in simple, easy-to-understand formats. Data visualization is a collection of two major components. First is data analysis and data presentation.

The below are some visualization software tools that are easy to use and allow the software do your task: iCharts, Fusion Charts Suit XT, Modest Maps, Raw, Tableau, Microsoft Power BI, Gephi, Plotly, Excel 2016, HighChartjs.

Visualizing and analyzing unstructured data and semi-structured data are done using search analytics. In search analytics, there are many technologies like search index, ElasticSearch and Apache Solr which access both structured and unstructured data. Search analytics is the one that allows us to filter from large datasets. Based on the search algorithm, the search will be accurate and uses search engines to improve the outputs. Zoomdata is a tool which is built for the unstructured data in big data along with the tools like Hadoop and Cassandra that are supported by big data.

Analytics facilitate the big data visualization in a great manner. The tight integration of visualization and analytics plays an important role to achieve the effective output for various big data applications. To serve the purpose, various big data visualization tools are also available that run on the Hadoop platform. Hadoop Common, Hadoop Distributed File System (HDFS), Hadoop YARN, and Hadoop MapReduce are some of the tools that help to efficiently analyze the big data. Pentaho, Flare, Jasper Reports, Dygraphs, Datameer Analytics Solution and Cloudera, ManyEyes, Platfora, and Tableau are some of the softwares developed for data visualization which can handle ZB (zettabytes) and PB (petabytes) data quite naturally but the major problem with these tools is the inadequate visualization.

Table of contents:

Narrative and Text Visualization: A Technique to Enhance Teaching Learning Process in Higher Education
Data Visualization and Analysis for Air Quality Monitoring Using IBM Watson IoT Platform
Comparative Analysis of Tools for Big Data Visualization and Challenges
Data Visualization Techniques: Traditional Data to Big Data
Data Visualization: Visualization of Social Media Marketing Analysis Data to Generate Effective Business Revenue Model
Applications of Visualization Techniques
Evaluation of IoT Data Visualization Tools and Techniques
Data Visualization: Experiment to Impose DDoS Attack and Its Recovery on Software-Defined Networks
Data Visualization of Software-Defined Networks During Load Balancing Experiment Using Floodlight Controller