About the Journal
The Journal of Big Data Analytics and Cloud Computing (JBDACC) is a multidisciplinary scholarly publication dedicated to advancing the theory, methodologies, and applications of big data analytics and cloud computing. It serves as a comprehensive platform for researchers, practitioners, and industry professionals to disseminate and exchange knowledge in these rapidly evolving fields.
The journal invites high-quality original research articles, reviews, case studies, and technical notes that explore the various aspects of big data analytics and cloud computing. It encompasses a wide range of topics, including but not limited to:
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Big Data Analytics:
- Data mining and knowledge discovery
- Machine learning and deep learning algorithms
- Predictive modeling and pattern recognition
- Sentiment analysis and opinion mining
- Text mining and natural language processing
- Social network analysis and graph mining
- Real-time and stream data analytics
- Visual analytics and data visualization
- Scalable and distributed data analytics
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Cloud Computing:
- Cloud architecture and infrastructure
- Cloud resource management and scheduling
- Virtualization techniques and technologies
- Cloud security and privacy
- Cloud-based data storage and retrieval
- Cloud-based machine learning and AI
- Fog and edge computing
- Serverless computing
- Cloud-native applications and microservices
The Journal of Big Data Analytics and Cloud Computing encourages contributions that demonstrate novel approaches, methodologies, and frameworks, as well as their practical applications and potential impact across various domains, such as healthcare, finance, e-commerce, transportation, social media, and more.
Current Issue
Journal of Big-Data Analytics and Cloud Computing
The Journal of Big-Data Analytics and Cloud Computing is a platform for disseminating advanced research at the confluence of big data analytics and cloud computing technologies. This journal is dedicated to publishing original research articles, comprehensive reviews, and insightful case studies that delve into both theoretical advancements and practical implementations within this dynamic field.
Submit Your ManuscriptThe journal's primary focus encompasses a broad spectrum of topics integral to big data analytics and cloud computing. Key areas of interest include:
- Scalable Data Processing Frameworks: Exploration of frameworks and architectures designed to handle large-scale data processing efficiently within cloud environments.
- Cloud-Based Data Storage Solutions: Investigations into innovative storage mechanisms that leverage cloud infrastructure to manage vast datasets effectively.
- Machine Learning Algorithms for Cloud Environments: Development and optimization of machine learning models tailored for deployment in cloud settings, addressing challenges such as scalability and resource allocation.
- Integration of Big Data Analytics with Cloud Infrastructure: Studies on the seamless integration of big data analytics tools and methodologies with cloud platforms to enhance performance and accessibility.
- Data Security and Privacy: Analyses of security protocols and privacy-preserving techniques pertinent to big data and cloud computing, ensuring the protection of sensitive information.
- Efficient Management of Large-Scale Data: Research on methodologies and tools aimed at the effective management, retrieval, and analysis of large datasets in cloud environments.
Authors are encouraged to submit manuscripts that present novel findings, propose innovative methodologies, or provide comprehensive reviews of existing literature. Submissions should adhere to the journal's formatting guidelines and undergo a rigorous peer-review process to ensure the publication of high-quality research.
View Submission GuidelinesThe journal caters to a diverse audience, including academic researchers, industry practitioners, and policymakers interested in the latest developments in big data analytics and cloud computing. By providing a platform for the exchange of knowledge and ideas, the journal aims to foster collaboration and innovation in this rapidly evolving field.
The journal's editorial board comprises esteemed scholars and industry experts with extensive experience in big data analytics and cloud computing. Their collective expertise ensures the maintenance of rigorous academic standards and the publication of impactful research.
Committed to the widespread dissemination of knowledge, the journal offers open-access publication options, allowing researchers and practitioners worldwide to access and benefit from the published content.
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