DFT 2022: Evolution of Web Driven Data Fabric Technology |
Submission link | https://easychair.org/conferences/?conf=dft2022 |
Abstract registration deadline | July 31, 2022 |
Submission deadline | September 30, 2022 |
The edited book on “Evolution of Web Driven Data Fabric Technology” comprehends the convergence of data generated from today’s revolutionary technologies like Artificial Intelligence, Machine Learning, Industrial Internet of Things, Augmented Reality and Virtual Reality. With the involvement of the various Edge Computing Devices in the retail and service sector, the data’s digital landscape is ever-growing in an unstructured way. Currently, the unstructured data silos generate various stages of business operation. The data silos so generated limit the optimal usage of the critical insights to be drawn in real-time; to restructure, reframe and revamp the industrial practices. The book captures the essence of Data Architecture while focussing on the semantic change in the future data landscape. It describes Web-driven Data Fabric operations and solutions for Industry 4.0 and automated trends evolving in market research. It also demonstrates the data harvesting and visualization tools for Scalable Data Fabric that can identify current market trends and their related use cases. Furthermore, it is a compilation of Rest APIs, Simulation Tools, Open-Sourced Platforms, essential Government Compliance strategies, Security, Privacy and Authentication Framework for the data fabric. This edited book will be a handbook for IT Industry Professionals like Data Scientists, Data Engineers, Data Analysts, Software Developers, Researchers, ML practitioners, AI practitioners, Cloud Computing practitioners, and Technology enthusiasts working in the domain of Modern Databases Architecture. There are only a few authored books on Data Fabric. The immense increase in the size and type of real-time data generated across various edge computing platforms results in an unstructured database. The internal data silos are hard to mitigate. Thus, the edited book on Evolution of Web Driven Data Fabric Technologies targets the parallelly growing technologies that make the data silos impertinent for growing business. The edited book focuses on the Data Fabric Techniques and Strategies to mitigate issues related to Modern Database Management.
Submission Guidelines
All chapters must be original and not simultaneously submitted to another journal or conference. The following chapter categories are welcome:
-
Table of Contents
Chapter 1 titled “Convergence of Modern Technologies for Data Architecture “will discuss the convergence strategies of Edge Computing, Cloud Computing and IoT.
Chapter 2 titled “Web Driven Data Operations for Industry 4.0” will describe the quick business solutions and management strategies for Scalable and Web Driven Data Fabric Applications.
Chapter 3 titled “Identifying Popular trends in the Data Driven World” surveys popular Data Fabrication Strategies for the Systematic Market Research and Getting Right Product-Policy Mix.
Chapter 4 titled “Harvesting and Visualization of Big Data Fabric” will provide the walkthrough for various Big Data Visualization Tools apart from Power BI and Tableau. A case study of IBM Cloud Pak will be discussed.
Chapter 5 titled “Data Fabric Use Cases” will lay emphasis on sustainable development and standardizing the circular economy for Green Cloud Computing Practices.
Chapter 6 includes “Data Fabric Technologies, and its Innovative Applications” in Education Sector, IIoT, Health Domain and Logistics, Disaster Management and Public Information Dissemination Strategies.
Chapter 7 titled” Enterprise Data” includes discussion on Enterprise Information Systems, Enterprise Data Governance, Enterprise Data Fabric Architecture, its related preservation and privacy policies.
Chapter 8 titled “Rest API for Web Driven Data Fabric” focusses on the useful Rest API for meaningful data exchange over Internet.
Chapter 9 discusses “Features, Key Challenges and Applications of Open-Source Data Fabric Platforms” that is reproducible, verifiable and Autonomous.
Chapter 10 titled “Simulation tools for Big Data Fabric” demonstrates the working of most popular simulation tools for Big Data Modelling.
Chapter 11 titled “Security, Privacy and Authentication Framework forWeb Driven Data Fabric” provides details about the Trust Management Policies, Framework for mitigating Trust Issues in Data Fabric.
Chapter 12 titled “Government Compliance Strategies for Web Driven DataFabric” provides study of Hyperledger fabric and its performance analysis for Blockchain Network in Framing Government Policies.
Editors
Dr. Vandana Sharma, Professor, Galgotias University, Greater Noida, India
Dr. Balamurugan Balusamy, Associate Dean – Student Engagement, Shiv Nadar University, Delhi-NCR Campus, India
Dr. J. Joshua Thomas, Assoc Professor, UOW Malaysia, KDU Penang University College.
Dr. L. Godlin Atlas, Assistant Professor, School of Computing Science and Engineering, Galgotias University