Intelligent Data Engineering and Autonomous Decision Systems for Next Generation  Digital Enterprises

Teemu Lehtinen; Teemu Lehtinen

doi:10.15662/IJSRAT.2025.0805004

Intelligent Data Engineering and Autonomous Decision Systems for Next Generation Digital Enterprises

Teemu Lehtinen

Abstract

Digital enterprises are increasingly driven by massive volumes of heterogeneous data, necessitating intelligent data engineering frameworks capable of real-time ingestion, transformation, and governance. Simultaneously, autonomous decision systems (ADS) powered by artificial intelligence (AI) and machine learning (ML) offer enterprises the ability to dynamically optimize operations, anticipate market trends, and reduce human intervention in decision-making processes. This paper presents a comprehensive framework for integrating intelligent data engineering pipelines with autonomous decision-making platforms, enabling scalable, adaptive, and secure digital enterprise architectures.

The proposed system leverages advanced data engineering techniques including data lakes, real-time stream processing, feature engineering, and automated metadata management. Autonomous decision modules employ reinforcement learning, predictive analytics, and AI-driven optimization to make operational and strategic decisions across enterprise workflows. Integration of explainable AI (XAI) ensures transparency, regulatory compliance, and trust in automated decision outcomes.

A multi-layered architecture encompassing data acquisition, storage, processing, ML model management, decision orchestration, and feedback loops is proposed. Emphasis is placed on scalability, resilience, security, and compliance, addressing challenges posed by heterogeneous data sources, cloud-native deployments, and regulatory constraints in financial, healthcare, and industrial contexts.

The methodology combines architectural modeling, simulation-based evaluation, and empirical validation using real-world datasets. Key performance indicators include data pipeline throughput, ML model accuracy, decision latency, system reliability, and operational cost efficiency. Preliminary results indicate that the proposed integration improves decision quality, accelerates operational workflows, and enhances data governance without significant trade-offs in computational overhead.

This research contributes a blueprint for next-generation digital enterprises that are not only data-driven but capable of autonomous and intelligent operational adaptation. By harmonizing intelligent data engineering with autonomous decision systems, enterprises can achieve enhanced agility, operational efficiency, and strategic foresight, positioning themselves competitively in increasingly dynamic digital ecosystems

Article Information

Journal	International Journal of Science, Research and Technology
Volume (Issue)	Vol. 8 No. 5 (2025): International Journal of Science, Research and Technology (IJSRAT)
DOI	https://doi.org/10.15662/IJSRAT.2025.0805004
Pages	14946-14954
Published	September 9, 2025
Copyright	All rights reserved
Open Access	This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite	Teemu Lehtinen (%2025). Intelligent Data Engineering and Autonomous Decision Systems for Next Generation Digital Enterprises. International Journal of Science, Research and Technology , Vol. 8 No. 5 (2025): International Journal of Science, Research and Technology (IJSRAT) , pp. 14946-14954. https://doi.org/10.15662/IJSRAT.2025.0805004

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