Analysis of Different Pattern Evaluation Procedures for Big Data Visualization in Data Analysis

2017 ◽  
pp. 453-461
Author(s):  
Srinivasa Rao Madala ◽  
V. N. Rajavarman ◽  
T. Venkata Satya Vivek
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Data Visualization ◽  
Evaluation Procedures ◽  
Big Data Visualization

Design and Implementation of Financial Big Data Visualization Analysis Platform

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Xi Chen ◽  
Bo Fan ◽  
Jie Zheng ◽  
Hongyan Cui
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Data Visualization ◽  
Production Efficiency ◽  
Big Data Analysis ◽  
Research Field ◽  
Visualization Analysis ◽  
Front End ◽  
Big Data Visualization ◽  
Analysis Platform

At present, it has become a hot research field to improve production efficiency and improve life experience through big data analysis. In the process of big data analysis, how to vividly display the results of the analysis is crucial. So, this paper introduces a set of big data visualization analysis platform based on financial field. The platform adopts the MVC system architecture, which is mainly composed of two parts: the background and the front end. The background part is built on the Django framework, and the front end is built with html5, css3, and JavaScript. The chart is rendered by Echarts. The platform can realize the classification of customers' savings potential through bank data, and make portraits of customers with different savings levels. The data analysis results can be dynamically displayed and interact wit

Big Data Visualization Tools and Techniques

2022 ◽  
pp. 590-621
Author(s):  
Obinna Chimaobi Okechukwu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Data Visualization ◽  
Data Sets ◽  
New Paradigm ◽  
Volume Velocity ◽  
Big Data Visualization ◽  
Visualization Tools ◽  
Tools And Techniques ◽  
Data Analysis Methods

In this chapter, a discussion is presented on the latest tools and techniques available for Big Data Visualization. These tools, techniques and methods need to be understood appropriately to analyze Big Data. Big Data is a whole new paradigm where huge sets of data are generated and analyzed based on volume, velocity and variety. Conventional data analysis methods are incapable of processing data of this dimension; hence, it is fundamentally important to be familiar with new tools and techniques capable of processing these datasets. This chapter will illustrate tools available for analysts to process and present Big Data sets in ways that can be used to make appropriate decisions. Some of these tools (e.g., Tableau, RapidMiner, R Studio, etc.) have phenomenal capabilities to visualize processed data in ways traditional tools cannot. The chapter will also aim to explain the differences between these tools and their utilities based on scenarios.

Big Data Visualization Tools and Techniques

2018 ◽  
pp. 465-496
Author(s):  
Obinna Chimaobi Okechukwu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Data Visualization ◽  
Data Sets ◽  
New Paradigm ◽  
Volume Velocity ◽  
Big Data Visualization ◽  
Visualization Tools ◽  
Tools And Techniques ◽  
Data Analysis Methods

In this chapter, a discussion is presented on the latest tools and techniques available for Big Data Visualization. These tools, techniques and methods need to be understood appropriately to analyze Big Data. Big Data is a whole new paradigm where huge sets of data are generated and analyzed based on volume, velocity and variety. Conventional data analysis methods are incapable of processing data of this dimension; hence, it is fundamentally important to be familiar with new tools and techniques capable of processing these datasets. This chapter will illustrate tools available for analysts to process and present Big Data sets in ways that can be used to make appropriate decisions. Some of these tools (e.g., Tableau, RapidMiner, R Studio, etc.) have phenomenal capabilities to visualize processed data in ways traditional tools cannot. The chapter will also aim to explain the differences between these tools and their utilities based on scenarios.

An Innovative Methodology for Big Data Visualization for Telemedicine

2019 ◽  
Vol 15 (1) ◽  
pp. 490-497 ◽  
Author(s):  
Antonino Galletta ◽  
Lorenzo Carnevale ◽  
Alessia Bramanti ◽  
Maria Fazio
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Big Data Visualization ◽  
Innovative Methodology

A Visual Insight Into Tweeting Activity Before and During Natural Disasters

2021 ◽  
Vol 12 (3) ◽  
pp. 19-33
Author(s):  
Shadi Maleki ◽  
Milad Mohammadalizadehkorde
Keyword(s):  
Social Media ◽  
Big Data ◽  
Spatial Distribution ◽  
Emergency Management ◽  
Data Visualization ◽  
High Dimensionality ◽  
High Complexity ◽  
Big Data Visualization ◽  
Disaster Studies ◽  
Insight Into

Big data provided by social media has been increasingly used in various fields of research including disaster studies and emergency management. Effective data visualization plays a central role in generating meaningful insight from big data. However, big data visualization has been a challenge due to the high complexity and high dimensionality of it. The purpose of this study is to examine how the number and spatial distribution of tweets changed on the day Hurricane Harvey made landfall near Houston, Texas. For this purpose, this study analyzed the change in tweeting activity between the Friday of Hurricane Harvey and a typical Friday before the event.

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