Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Dabbir, Rupesh; Logeshwaran, J. Title A name given to the resource Integrating Big Data Management with Machine Learning in Cloud Environments Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Networks and Cryptology, NETCRYPT 2025;pp.443-447 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/NETCRYPT65877.2025.11102667" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/NETCRYPT65877.2025.11102667</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105015469770?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105015469770?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Dabbir R., Google LLC, San Jose, CA, United States; Logeshwaran J., Christ University, Department of Computer Science, Karnataka, Bengaluru, 560029, India Description An account of the resource In past years, the consideration of cloud environments for big data management and machine learning techniques has increased exponentially. However, the massive amount of data that is made by companies and Internet of Things (IoT) devices has presented the industry with a challenge in storage. In addition, conventional data management methods are unable to manage the complexity, diversity, and volume of this big data. Consequently, cloud environments integrate big data management and machine learning techniques. Combining big data management through cloud environments equipped with machine learning has multiple benefits. First, it is an efficient way to process and analyze large datasets in a distributed and scalable manner. Second, it helps businesses to provide insights and make time to make datadriven decisions. Thirdly, it enables the system to learn from data on an ongoing basis, which helps improve the quality and accuracy of the data. Now, this integration also enhances the overall performance of cloud systems as data management tasks are automated, minimizing manual efforts. Utilizing Big Data Management and Machine Learning Techniques in Cloud Environment to Address the Drawbacks of Conventional Data Management Approaches and Exploit the Value of Big Data These two technologies, when integrated, will allow the enterprise to manage significant amounts of data and derive important insights to arrive at better decisions. Cloud environments provide the automation and scalability required to push this integration further and change considerable data use in businesses. 2025 IEEE. Subject The topic of the resource Automation; Cloud Systems; Complexity; Conventional Data; Diversity; Internet Of Things Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152605-4; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online