The Future of Data Platforms: AI-Driven Automation and Self-Optimizing Systems

Authors

  • Madhuri Koripalli University of Louisiana, USA

DOI:

https://doi.org/10.32996/jcsts.2025.7.2.50

Keywords:

Metadata intelligence, Self-healing pipelines, Predictive optimization, Embedded governance, Autonomous data platforms

Abstract

The evolution of data platforms is entering a new era characterized by AI-driven automation and self-optimizing capabilities that address the unprecedented challenges of exponential data growth. As organizations struggle with increasingly complex data ecosystems, traditional management approaches are becoming inadequate. This document presents how next-generation data platforms leverage artificial intelligence to transform data operations through four key innovations: metadata intelligence serving as the nervous system of modern platforms; self-healing data pipelines that autonomously detect and resolve issues; predictive resource optimization that anticipate computational needs before they arise; and embedded governance frameworks that make compliance an integral rather than external function. These advancements collectively shift data management from reactive to proactive paradigms, enabling organizations to derive more excellent value from their information assets while reducing manual intervention and operational costs.

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Published

2025-04-25

Issue

Section

Research Article

How to Cite

Madhuri Koripalli. (2025). The Future of Data Platforms: AI-Driven Automation and Self-Optimizing Systems. Journal of Computer Science and Technology Studies, 7(2), 483-488. https://doi.org/10.32996/jcsts.2025.7.2.50