Analysis of the Impact of Data Flow Mechanisms on Corporate Competitiveness Based on Intelligent Business Platforms
Keywords:
data flow, corporate competitiveness, intelligent business platforms, data architecture, stream processing, data virtualization, ETLAbstract
This review paper examines the impact of data flow mechanisms on corporate competitiveness within intelligent business platforms. With the proliferation of data-driven decision-making, understanding how data flows through an organization’s systems has become critical for sustained competitive advantage. The review synthesizes existing literature on data flow architectures, including ETL pipelines, stream processing frameworks, and data virtualization techniques. It analyzes how these mechanisms influence key competitive factors such as operational efficiency, innovation speed, and customer responsiveness. Special attention is given to the integration of artificial intelligence and machine learning within these platforms, addressing both the opportunities and challenges they present. Furthermore, the paper explores the limitations and potential pitfalls of current data flow approaches, proposes areas for future research, and emphasizes the strategic importance of aligning data flow design with overall business objectives. This review caters to researchers and practitioners interested in leveraging data flow mechanisms to enhance corporate competitiveness in the age of intelligent business platforms.References
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