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calendar31 Dekabr 2025
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CHALLENGES OF INFORMATION SYSTEMS INTEGRATION IN BIG DATA ENVIRONMENTS AND THEIR SOLUTIONS

Field of Science:Artificial IntelligenceComputational Theory and MathematicsComputer Graphics and Computer-Aided DesignComputer Networks and CommunicationsInformation SystemsSignal ProcessingSoftware
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ARTICLE ANNOTATION

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In the era of Big Data, the integration of information systems is a complex multi-layered process that involves combining heterogeneous data sources, ensuring semantic consistency, supporting real-time operations, achieving scalability, and maintaining interoperability among distributed systems. This study provides a systematic analysis of the key challenges associated with data integration in large-scale environments and proposes an enhanced integration model based on distributed computing technologies (Hadoop, Spark), microservices architecture, containerization (Docker, Kubernetes), and ontology-driven data modeling. Experimental evaluation demonstrates significant improvements over traditional approaches: throughput increased by a factor of 2.4, latency decreased by 35–50%, semantic matching accuracy improved by 18–27%, and fault tolerance increased by 40%. These results confirm that the proposed model offers an efficient and robust solution for integrating information systems operating in Big Data environments, including corporate platforms, IoT infrastructures, and digital transformation ecosystems.

AUTHORS

O.Xolmuminov

"O`ZBEKISTON DAVLAT JAHON TILLARI UNIVERSITETI" DAVLAT MUASSASASI

SH.Qodirberganova

"O`ZBEKISTON DAVLAT JAHON TILLARI UNIVERSITETI" DAVLAT MUASSASASI

Tags

# systems# data# integration# information# architecture# semantic# interoperability# processing# big# real-time# heterogeneity# microservices# containerization# nosql# scalability

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References

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