Workflow-Based Big Data Analytics in The Cloud Environment Present Research Status and Future Prospects
Samiya Khan, Kashish Ara Shakil, Mansaf Alam

TL;DR
This paper reviews the current state and future prospects of workflow-based big data analytics in cloud environments, highlighting its importance for complex scientific and business data processing tasks.
Contribution
It provides a comprehensive overview of existing research and identifies future research directions in workflow-based big data analytics in cloud settings.
Findings
Workflow enhances efficiency in big data analytics
Cloud environment enables scalable data processing
Future research should focus on automation and optimization
Abstract
Workflow is a common term used to describe a systematic breakdown of tasks that need to be performed to solve a problem. This concept has found best use in scientific and business applications for streamlining and improving the performance of the underlying processes targeted towards achieving an outcome. The growing complexity of big data analytical problems has invited the use of scientific workflows for performing complex tasks for specific domain applications. This research investigates the efficacy of workflow-based big data analytics in the cloud environment, giving insights on the research already performed in the area and possible future research directions in the field.
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Taxonomy
TopicsScientific Computing and Data Management · Distributed and Parallel Computing Systems · Cloud Computing and Resource Management
