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Intelligent Data Engineering Architectures for Scalable Real-Time Enterprise Analytics Using Secure Multi-Cloud Platforms

Dr Anisha Tandon

Department of Computer Science, Jagan Institute of Management Studies (JIMS), Rohini, New Delhi, India

Abstract

The rapid growth of enterprise data generated by applications, connected devices, business transactions, and digital services has created a strong demand for data engineering architectures capable of delivering scalable, real-time analytics. Traditional centralized data infrastructures often face limitations related to scalability, latency, interoperability, security, and vendor dependency. Intelligent data engineering architectures address these challenges by combining distributed processing, cloud-native services, real-time streaming, artificial intelligence, automated data governance, and multi-cloud deployment strategies. This paper examines an architecture for enterprise analytics that integrates secure data ingestion, stream and batch processing, lakehouse-oriented storage, metadata management, machine learning, and analytics services across multiple cloud environments. Particular attention is given to data encryption, identity and access management, zero-trust principles, policy-based governance, workload isolation, and resilient cross-cloud orchestration. The proposed methodology evaluates architectural requirements, identifies appropriate processing and security components, develops an integrated multi-cloud framework, and assesses the architecture according to scalability, latency, reliability, interoperability, security, and operational efficiency. The approach emphasizes intelligent workload placement and automated resource management to support changing enterprise workloads. Such architectures can enable organizations to transform heterogeneous data into timely analytical insights while maintaining security, governance, resilience, and flexibility across complex multi-cloud environments.

Article Information

Journal

International Journal of Emerging Trends in Engineering and Management Research

Volume (Issue)

Vol. 11 No. 5 (2026): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR)

DOI

https://doi.org/10.15662/ijetemr.2026.1105005

Pages

22007-22015

Published

September 7, 2026
Copyright

Open Access

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Dr Anisha Tandon (%2026). Intelligent Data Engineering Architectures for Scalable Real-Time Enterprise Analytics Using Secure Multi-Cloud Platforms. International Journal of Emerging Trends in Engineering and Management Research , Vol. 11 No. 5 (2026): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) , pp. 22007-22015. https://doi.org/10.15662/ijetemr.2026.1105005

References

1. Samek, W., Montavon, G., Vedaldi, A., Hansen, L. K., & Müller, K.-R. (Eds.). (2019). Explainable AI: Interpreting, explaining and visualizing deep learning. Springer.
2. Hossain, I., Hossain, M. S., Rasul, I., Prince, N. U., Datta, A., & Akand, A. R. (2026, June). Machine Learning-Based Evaluation of Password Security and User Awareness for Cyber Risk Prevention. In 2026 Third International Conference on Innovations in Cybersecurity and Data Science (ICICDS) (pp. 499-504). IEEE.
3. Raja, G. V. (2022). AI Enabled Cloud and Data Engineering Frameworks for Secure, Scalable, and Intelligent Cyber Physical Analytics Systems. International Journal of Research and Applied Innovations, 5(4), 7395-7409.
4. Selvarajan, K. (2025). AI-powered big data platforms for enterprise analytics. International Journal of Computer Technology and Electronics Communication, 8(2), 10490–10496.
5. Srikanth, V., Walia, R., Augustine, P. J., Simla, J., & Jegajothi, B. (2022, March). Chaotic Whale Optimization based Node Localization Protocol for Wireless Sensor Networks Enabled Indoor Communication. In 2022 International Conference on Electronics and Renewable Systems (ICEARS) (pp. 702-707). IEEE.
6. Maroju, P. K., & Mudunuri, L. N. R. (2025, October). Generative AI as a Cyber Weapon: Synthetic Identity Fraud and Phishing at Scale. In International Conference on Artificial Intelligence and Networking (pp. 573-585). Cham: Springer Nature Switzerland.
7. Yadavalli, V. R. (2024). Hypercare signal fusion for early instability detection in SAP S/4HANA and EWM go-lives. International Research Journal of Innovative Engineering, 8(5), 15423–15437.
8. Kalakoti, M. K. R., & Kalakoti, M. K. R. (2025). AI-augmented self-healing infrastructure: Combining health probes with remediation playbooks. Journal of Information Systems Engineering and Management, 10(58s), 1147-1157.
9. Polamarasetty, V. K. (2025). Scalable Workday benefits integration frameworks for enterprise HR technology. International Journal of Computer Technology and Electronics Communication, 8(2), 10483–10489.
10. Goyal, K. K., Hebbar, K. S., & Mali, R. K. (2026, March). AI Modernization Enabled by Cloud-Native and Edge-Intelligent Architectures. In International Conference on Information Technology and Artificial Intelligence (pp. 102-114). Cham: Springer Nature Switzerland.
11. Venkatasalam, K., Rajendran, P., & Thangavel, M. (2019). Improving the accuracy of feature selection in big data mining using accelerated flower pollination (AFP) algorithm. Journal of medical systems, 43(4), 96.
12. Devineni, A., Prabagaran, A., Mali, R. K., Mishra, M. K., Nekkalapudi, K., & Velu, R. (2026, June). Intelligent Incident Prediction in Banking Cloud Operations: A Machine Learning Framework for Proactive SRE Response. In 2026 5th International Conference on Computer Networks, Big Data and IoT (ICCBI) (pp. 1072-1078). IEEE.
13. Gopinathan, V. R. (2025). Privacy-Preserving Federated AI for Secure Digital Enterprises across Hybrid Cloud Computing Ecosystems and Distributed Intelligence. International Journal of Computer Technology and Electronics Communication, 8(6), 11999-12007.
14. Chundi, V. R. K., Agarwal, V., & Arya, P. (2025, November). Green AI for Sustainable Supply Chains: Challenges in Emerging Economies. In 2025 International Conference on Computational Engineering, Sensing Technology and Management (ICCETM) (pp. 1-5). IEEE.
15. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
16. Li, Q., Li, Z., Liu, W., He, X., & Pan, Y. (2025). Sarcasm-GPT: advancing sarcasm detection with large language models. The Computer Journal, 68(10), 1523-1534.
17. Bellundagi, M. (2023). Design of an Intelligent Clinical Decision Support System Using Machine Learning Techniques. International Journal of Research and Applied Innovations, 6(6), 10075-10081.
18. Tarigoppula, S. (2021). Policy-driven autonomous infrastructure provisioning: A framework for enterprise cloud governance using infrastructure as code. International Journal of Emerging Trends in Engineering and Management Research, 6(5), 10361–10369.
19. Bitragunta, S. L. V. (2025). AI-assisted stability analysis of microgrids with distributed renewable energy sources. International Journal of Advanced Engineering Science and Information Technology, 8(1), 15681–15686.
20. Mathew, A. (2021). Artificial intelligence and cognitive computing for 6G communications & networks. International Journal of Computer Science and Mobile Computing, 10(3), 26-31.
21. Tatavarthi, S., Koilakonda, R. R., Bikkavolu, V., Tarakampet, S. K., & Gudala, M. (2026, April). Enterprise Governance for Generative AI: Prompt Lifecycle and Secure Middleware. In 2026 International Conference on Artificial Intelligence, Systems, and Emerging Technologies (ICAISET) (pp. 1-6). IEEE.
22. Ahuja, D. (2023). Multi-Cloud Management Strategies: Tools, Challenges, and Implementation Methods. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, 9(10), 493-506.
23. Vedula, J., Davlatovich, P. S., Aminqulov, S., Gururani, S., Babaxanovna, D. A., & Masharipova, G. (2025, November). Real-Time AI-Driven Monitoring of ICU Patients for Early Detection of Acute Respiratory Distress Syndrome (ARDS). In 2025 2nd Global AI Summit-International Conference on Artificial Intelligence and Emerging Technology (AI Summit) (pp. 449-454). IEEE.
24. Soundappan, S. J. (2021). Integrated Artificial Intelligence Framework for Enterprise Cloud Modernization and Intelligent Threat Management Systems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 4(4), 5274-5284.
25. Pothuri, M. K. (2026). Predicting Very High-Cost Claimants Using Symmetry ETG/PEG Feature Engineering Combined with Advanced Machine Learning. International Journal of AI, BigData, Computational and Management Studies, 352-357.
26. Kargeti, H. (2026, February). Automating Enterprise Vulnerability Exposure: SCAP-Based Asset-CVE Linkage with Social Signal Triage for Cyber Defense. In 2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) (pp. 1-6). IEEE.
27. Anand, L. (2023). Machine Learning Enabled Enterprise Integration through Intelligent API Governance Secure Cloud Infrastructure and Automated Operations. International Journal of Research and Applied Innovations, 6(3), 5972-5979.
28. Neela, S. (2022). Semantic Interoperability in Real-Time Enterprise Integration Using Middleware Abstractions. American International Journal of Computer Science and Technology, 4(6), 56-66.
29. Mohile, A. (2026, April). Zero Trust Architectures for Securing Foundation Model Lifecycles in Enterprise AI Systems. In 2026 3rd International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE) (pp. 1-6). IEEE.
30. Shrestha, G., Ivanov, T., Vemireddy, K., Pyayt, A., & Gubanov, M. (2026, July). Hemolix. TabGen: Optimized Table Generation from Documents. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026) (pp. 1055-1066).
31. Ravichandran, S., & Kandasamy, V. (2025). Optimized Attention Augmented Residual Convolutional Neural Network with Fa-Resnet for Fabric Defect Detection. Journal of Control Engineering and Applied Informatics, 27(4), 3-15.
32. Ramasamy, M. (2025). AI-driven automation and platform orchestration in network engineering and cloud infrastructure. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(3), 12170–12174.
33. Devineni, A., Pochincharla, S., & Muppalla, L. K. (2022). A Telemetry-Fusion Framework for Proactive Incident Detection in Multi-Tenant Financial Cloud Platforms. International Journal of Advances in Signal And Image Sciences, 13-18.
34. Shaik, N. (2025). Dynamic healthcare intelligence: Integrating AI predictive analytics with Kubernetes scaling for enhanced patient outcomes. International Journal of Engineering & Extended Technologies Research, 7(2), 9715–9720.
35. Selvarajan, K. (2025). Next-generation AI-driven big data platforms. International Journal of Research Publications in Engineering, Technology and Management, 8(2), 11831–11836.
36. Jayaraman, S., Rajendran, S., & P, S. P. (2019). Fuzzy c-means clustering and elliptic curve cryptography using privacy preserving in cloud. International Journal of Business Intelligence and Data Mining, 15(3), 273-287.
37. Ambalakannu, M. (2025, November). Next-Gen Healthcare Claims Optimization: DL-Based ResAttBiL Integrated with CDC, Modular Design, and Data Observability. In 2025 5th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS) (pp. 980-985). IEEE.
38. Raja, G. V. (2022). AI Enabled Cloud and Data Engineering Frameworks for Secure, Scalable, and Intelligent Cyber Physical Analytics Systems. International Journal of Research and Applied Innovations, 5(4), 7395-7409.
39. Reddy, K. V. (2021). UVM methodology for industry-specific applications using AI in hardware verification. International Journal of Science, Research and Technology, 4(3), 5731–5744.