Modern Enterprise Intelligence Systems: Engineering Adaptive, Multi-Cloud Data Platforms

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Authors

Velangani Divya Vardhan Kumar Bandi
Director AI/ML Engineering
https://orcid.org/0009-0008-7949-5670

Keywords:

Cloud Data, Multi-Cloud Platforms, Big Data, Machine Learning, Lifecycle Management, Predictive Analytics, Healthcare

Synopsis

The enterprise data landscape has undergone a profound transformation over the past decade. What began as centralized data warehouses has evolved into a complex ecosystem of distributed systems, cloud platforms, and real-time analytics engines. Today's organizations face an unprecedented challenge: how to build intelligent systems that can adapt to rapidly changing business needs while operating seamlessly across multiple cloud environments. This book emerges from years of hands-on experience designing and implementing large-scale data platforms for global enterprises. It reflects the hard-earned lessons of navigating the shift from monolithic architectures to distributed, cloud-native systems and the realization that traditional approaches to data engineering are no longer sufficient. Modern enterprise intelligence systems must be adaptive by design. They need to handle data from countless sources, process information at various velocities, and serve diverse analytical workloads all while maintaining governance, security, and cost efficiency. The multi-cloud reality adds another layer of complexity: enterprises rarely operate on a single platform, instead leveraging AWS, Azure, and Google Cloud simultaneously to optimize for capability, resilience, and negotiating leverage.

This book provides a practical framework for engineering such systems. Rather than advocating for specific technologies, it focuses on architectural patterns, design principles, and decision-making frameworks that remain relevant regardless of your technology stack. You'll find actionable guidance on building data meshes, implementing event-driven architectures, orchestrating cross-cloud workflows, and establishing effective data governance. Whether you're a data engineer modernizing legacy systems, an architect planning your organization's next-generation platform, or a technical leader navigating cloud strategy, this book offers the insights needed to build enterprise intelligence systems that don't just meet today's requirements but adapt to tomorrow's uncertainties.

Chapters

References

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J. Gray and A. Reuter, “Transaction Processing: Concepts and Techniques,” Morgan Kaufmann, 1992.

Downloads

Front Pages

Published

14 February 2026
Copyright (c) 2026 Velangani Divya Vardhan Kumar Bandi

Details about the available publication format: E-Book

E-Book

ISBN-13 (15)

978-93-7185-496-2

Details about the available publication format: Book (Paperback)

Book (Paperback)

ISBN-13 (15)

978-93-7185-079-7

How to Cite

Bandi, V. D. V. K. . (2026). Modern Enterprise Intelligence Systems: Engineering Adaptive, Multi-Cloud Data Platforms. Deep Science Publishing. https://doi.org/10.70593/978-93-7185-496-2
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