Building End-to-End Analytics Pipelines for Corporate Decision Support

Abstract

In today’s competitive business landscape, organizations require effective analytics pipelines to transform raw data into actionable insights that can guide decision-making. An end-to-end analytics pipeline integrates various stages of data processing, from data collection and cleaning to analysis and visualization. This paper explores the design, development, and implementation of such pipelines, focusing on how they can enhance corporate decision support. The research aims to demonstrate how organizations can leverage these pipelines to drive data-driven decision-making, increase operational efficiency, and foster innovation. The methodology involves a comprehensive review of existing frameworks, followed by the design and implementation of a prototype pipeline for decision support in a corporate environment. Finally, the results show that the implementation of these pipelines can significantly enhance decision-making by providing real-time insights and predictive analytics.