International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Architecting Real-time Enterprise Data Fabrics: Advanced Oracle Golden Gate Strategies for Heterogeneous Integration and AI/ML Data Pipelines

Author(s) Mr. Sridhar K Korimilli
Country United States
Abstract The presented research explores how the combination of AI-augmented streaming data infrastructures with CDC or data integration solution provided by Oracle GoldenGate may be used to provide low-latency, policy-conscious data integration. The paper assesses the performance implications of AI-driven transformations, detection of anomaly and orchestration in multi-cloud, heterogeneous environments.
The experimental practice will indicate a 47-52 percent latency in the end-to-end purpose and a 1.8X pace of throughput of typical ETL pipelines. AI-empowered governance mechanisms allowed the reporting cycle on compliance to be 35 percent faster with an accuracy of 99.9 percent of data. Access to security features, such as encryption, RBAC and real-time threat detection were also widely and productively deployed without performance impairment.
Quantifying the time to process, transformation effectiveness as well as scalability show that the orchestration that comes with an AI can dynamically scale in response to workload variability and satisfy regulatory needs. The results demonstrate the promise of enterprise architectures to become self-optimizing, rules-aware data fabrics, able to maintain velocity and reliability of mission-Imperative activity.
Keywords Oracle, Data Pipelines, ML, AI, Heterogeneous Data Integration, Latency, Golden Gate, Enterprise
Field Computer > Data / Information
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-10-18
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.58395
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E-ISSN 2582-2160
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