Harnessing Predictive Analytics for Strategic Foresight: A Comprehensive Review of Techniques and Applications in Transforming Raw Data to Actionable Insights

Folashade Gloria Olaniyi, O. O. Olaniyi, Chinasa Susan Adigwe, Anthony Idoko Abalaka, Nishant Hemantkumar Shah
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Abstract

In an era characterized by an unprecedented influx of data, the skill to extract actionable insights from this deluge has become paramount for organizations across diverse industries. The study seeks to address this challenge by exploring the transformative potential of predictive analytics. The research problem at the heart of this study revolves around the need to leverage data not merely as a historical repository but as a predictive tool for informed decision-making. In pursuit of this goal, a comprehensive literature review is undertaken, dissecting the evolution of data analytics, and highlighting the pivotal role of predictive analytics in today's data-driven landscape. This review identifies gaps in current knowledge, emphasizing the need for a deeper understanding of predictive analytics’ practical applications and implications. Methodologically, this research employs a multi-faceted approach. It incorporates case studies from diverse sectors, including healthcare, finance, marketing, and government, to exemplify how predictive analytics shapes strategies, optimizes operations, and enhances user experiences. Additionally, the study delves into the latest developments and trends in data analytics, surveying cutting-edge tools and techniques that empower organizations to navigate the complex terrain of big data. Key findings from this investigation underscore the profound impact of predictive analytics. It reveals that organizations adopting predictive analytics experience a marked improvement in their ability to anticipate future trends, optimize resource allocation, and mitigate risks effectively. Real-world examples demonstrate how predictive analytics can revolutionize patient care, financial decision-making, marketing campaigns, and public policy formulation, among other domains. The implications of this research are far-reaching. It underscores organizations' need to invest in predictive analytics as a strategic asset that enhances competitiveness and fosters innovation. As data continues to burgeon, embracing predictive analytics emerges as a decisive step toward navigating the complexities of the data-driven age.
利用预测分析进行战略前瞻:将原始数据转化为可操作见解的技术和应用综述
在这个以前所未有的数据涌入为特征的时代,对于各行各业的组织而言,从数据洪流中提取可行见解的技能已变得至关重要。本研究旨在通过探索预测分析的变革潜力来应对这一挑战。本研究的核心问题是,不仅要将数据作为历史资料库,还要将其作为知情决策的预测工具。为了实现这一目标,我们进行了全面的文献综述,剖析了数据分析的演变过程,并强调了预测分析在当今数据驱动型环境中的关键作用。这篇综述指出了当前知识中的空白,强调了深入了解预测分析的实际应用和影响的必要性。在方法上,本研究采用了多方面的方法。它结合了医疗保健、金融、营销和政府等不同领域的案例研究,举例说明了预测分析如何塑造战略、优化运营和提升用户体验。此外,该研究还深入探讨了数据分析的最新发展和趋势,调查了使企业能够驾驭复杂的大数据领域的尖端工具和技术。这项调查的主要发现强调了预测分析的深远影响。调查显示,采用预测分析技术的企业在预测未来趋势、优化资源配置和有效降低风险方面的能力有了显著提高。现实世界中的例子证明了预测分析如何彻底改变病人护理、财务决策、营销活动和公共政策制定等领域。这项研究意义深远。它强调了企业将预测分析作为一种战略资产进行投资的必要性,这种资产可以增强竞争力并促进创新。随着数据的不断激增,采用预测分析技术已成为驾驭数据驱动时代复杂局面的决定性一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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