scholarly journals Eminent Data Visualization Tools for Integration of Big Data with IoT

2021 ◽  
pp. 131-134
Author(s):  
Mrs Poonam ◽  
Mrs. Aditi Mittal
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Total Mass ◽  
The Internet ◽  
Data Generation ◽  
Exponential Increase ◽  
Visualization Tools ◽  
Technical Revolution

In the 2020 era, there is an exponential increase in the number of devices and machines that are connecting with the internet to transmit information for analysis as well as increasing the rate of data generation. Big data and IoT are two new trends, combining them creates a technical revolution. Approx, ⅛ of an iceberg’s total mass is visible above water. ⅞ of its part stretches into the ocean and is hidden from our view. Similarly, we have many devices which are connected with the internet and huge amounts of data in any field is not entirely used. Now we have large amounts of dark data. Hence ,there is a need for analysis of this data and embed the big data with IoT. In this Paper. We are discussing terms about Big Data and IoT, Functioning of IoT with big data, Role of big data in IoT and Some data visualization tools for representing that data.

Big Data Analytics in Bioinformatics

Biotechnology ◽  
2019 ◽  
pp. 1967-1984
Author(s):  
Dharmendra Trikamlal Patel
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Annual Growth ◽  
Predictive Analysis ◽  
The Internet ◽  
Data Generation ◽  
Intelligent Devices ◽  
The Internet Of Things

Voluminous data are being generated by various means. The Internet of Things (IoT) has emerged recently to group all manmade artificial things around us. Due to intelligent devices, the annual growth of data generation has increased rapidly, and it is expected that by 2020, it will reach more than 40 trillion GB. Data generated through devices are in unstructured form. Traditional techniques of descriptive and predictive analysis are not enough for that. Big Data Analytics have emerged to perform descriptive and predictive analysis on such voluminous data. This chapter first deals with the introduction to Big Data Analytics. Big Data Analytics is very essential in Bioinformatics field as the size of human genome sometimes reaches 200 GB. The chapter next deals with different types of big data in Bioinformatics. The chapter describes several problems and challenges based on big data in Bioinformatics. Finally, the chapter deals with techniques of Big Data Analytics in the Bioinformatics field.

Big Data, Artificial Intelligence, and the Internet of Things in Cross-Border E-Commerce

2021 ◽  
pp. 257-272
Author(s):  
Aboobucker Ilmudeen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Economic Globalization ◽  
The Internet ◽  
Technological Revolution ◽  
Cross Border ◽  
Wide Range ◽  
The Internet Of Things

Today, the terms big data, artificial intelligence, and internet of things (IoT) are many-fold as these are linked with various applications, technologies, eco-systems, and services in the business domain. The recent industrial and technological revolution have become popular ever before, and the cross-border e-commerce activities are emerging very rapidly. As a result, it supports to the growth of economic globalization that has strategic importance for the advancement of e-commerce activities across the globe. In the business industry, the wide range applications of technologies like big data, artificial intelligence, and internet of things in cross-border e-commerce have grown exponential. This chapter systematically reviews the role of big data, artificial intelligence, and IoT in cross-border e-commerce and proposes a conceptually-designed smart-integrated cross-border e-commerce platform.

scholarly journals Graph structures for data visualizations

2021 ◽  
Vol 6 (2) ◽  
pp. 24-31
Author(s):  
Stefana Janićijević ◽  
Vojkan Nikolić
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Data Types ◽  
Current State ◽  
Graph Structures ◽  
Big Data Visualization ◽  
Visualization Tools ◽  
Graph System ◽  
Data Visualizations

Networks are all around us. Graph structures are established in the core of every network system therefore it is assumed to be understood as graphs as data visualization objects. Those objects grow from abstract mathematical paradigms up to information insights and connection channels. Essential metrics in graphs were calculated such as degree centrality, closeness centrality, betweenness centrality and page rank centrality and in all of them describe communication inside the graph system. The main goal of this research is to look at the methods of visualization over the existing Big data and to present new approaches and solutions for the current state of Big data visualization. This paper provides a classification of existing data types, analytical methods, techniques and visualization tools, with special emphasis on researching the evolution of visualization methodology in recent years. Based on the obtained results, the shortcomings of the existing visualization methods can be noticed.

scholarly journals THEORIES AND ANTECEDENTS OF KNOWLEDGE SHARING BEHAVIOUR IN VIRTUAL COMMUNITY: A SYSTEMATIC REVIEW

2020 ◽  
Vol 11 (10) ◽  
pp. 32-51
Keyword(s):  
Systematic Review ◽  
Big Data ◽  
Web 2.0 ◽  
Knowledge Sharing ◽  
Industry 4.0 ◽  
Virtual Community ◽  
The Internet ◽  
Knowledge Based ◽  
Comprehensive Study

Virtual Community (VC) is regarded as the best platform for professionals in various fields to share their expertise and knowledge. Since the escalation of web 2.0 and the internet within the last decade and the booming interest in big data and expansion of industry 4.0, VC is deemed as an ideal proxy for practitioners to share and earned instant knowledge that can be implemented within business activities and day to day application. Despite this emerging interest, there has been no comprehensive study on the overall antecedents of KS in VC. Applying for a systematic review, a total of 68 relevant articles that discusses knowledge sharing (KS) via VC are evaluated. Several central themes of theories applied in this field within the literature are discussed on its importance and relevance. Important antecedents are also reviewed on its practicality and implementation in understanding the role of KS in VC. The implication of this review would benefit stakeholders in maintaining the sustainability of VC as the platform for a knowledge-based society.

Big Data Analytics in Bioinformatics

2018 ◽  
pp. 321-338
Author(s):  
Dharmendra Trikamlal Patel
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Annual Growth ◽  
Predictive Analysis ◽  
The Internet ◽  
Data Generation ◽  
Intelligent Devices ◽  
The Internet Of Things

Voluminous data are being generated by various means. The Internet of Things (IoT) has emerged recently to group all manmade artificial things around us. Due to intelligent devices, the annual growth of data generation has increased rapidly, and it is expected that by 2020, it will reach more than 40 trillion GB. Data generated through devices are in unstructured form. Traditional techniques of descriptive and predictive analysis are not enough for that. Big Data Analytics have emerged to perform descriptive and predictive analysis on such voluminous data. This chapter first deals with the introduction to Big Data Analytics. Big Data Analytics is very essential in Bioinformatics field as the size of human genome sometimes reaches 200 GB. The chapter next deals with different types of big data in Bioinformatics. The chapter describes several problems and challenges based on big data in Bioinformatics. Finally, the chapter deals with techniques of Big Data Analytics in the Bioinformatics field.

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.

The Role of the Profile and the Digital Identity on the Mobile Content

2019 ◽  
pp. 1645-1664
Author(s):  
Ana Serrano Tellería
Keyword(s):  
Big Data ◽  
User Profile ◽  
The Internet ◽  
Digital Identity ◽  
Information Economy ◽  
And Diffusion

The (re)construction of the user profile and the digital identity resulting from both conscious and unconscious activity on the Internet is directly linked to the process of creation and diffusion of content. Many times, neither the users-prosumers are aware of this process nor are the authors cognizant of the original content, as new authors – humans as well as machines - cover the relations established between the users, their content, their activity online and the combination of these. Big data and information economy are not just consequences of the possibility of collecting as much information as possible about users. Instead, they provide a quasi unlimited means of mapping and shaping every movement of our behavior and lives through devices and technologies. Therefore, the aim of this chapter is to understand how users handle this liquid ecosystem and its relationship with the evolution of mobile content, considering the different rhythms and dimensions.

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