In a world where data is the new infrastructure, The Great Data Shift is the definitive guide to understanding the sweeping transformation of data engineering and its intersection with artificial intelligence. This enterprise-grade, deeply technical book charts the evolution from OLTP systems and traditional data warehouses to the rise of cloud-native platforms, real-time data pipelines, and autonomous AI agents.

Written for seasoned professionals, architects, and advanced practitioners, it demystifies the complexities behind lakehouses, feature stores, vector databases, semantic layers, and agentic AI. With a balanced mix of historical insight, architectural patterns, and forward-looking strategies, this book prepares readers to lead in a landscape where data systems are not just pipelines, but intelligent ecosystems.

Whether you're modernizing legacy architectures or designing AI-driven platforms, The Great Data Shift equips you to engineer the future of data with clarity, confidence, and foresight.

About the Authors

Rohit Muthyala is a Principal Software Engineer at ZoomInfo, specializing in large-scale data engineering, real-time platforms, and applied machine learning. He designs and leads petabyte-scale data pipelines, streaming entity-resolution systems, and ML/LLM-powered analytics that power core product experiences and go-to-market intelligence. His work spans Apache Beam/Dataflow, Flink, Kafka, BigQuery, and modern data lake/warehouse architectures, with a strong focus on correctness, cost-efficiency, and observability in production systems. Rohit has published peer?reviewed research in top IEEE venues, including work on deep learning for automated industry classification, job matching using skills and company attributes, and quantum-inspired clustering algorithms. He is a Senior Member of IEEE and serves as a reviewer for multiple international conferences and workshops in AI, data engineering, and software systems. He holds a B.Tech (Honours) in Computer Science from the Indian Institute of Technology (IIT) Hyderabad and an M.S. in Computer Science from New York University's Courant Institute, where he focused on machine learning, computer vision, and big data systems.

Srinivas Mudireddy is a Product and Tech leader with experience across large-scale operations, applied AI, finance, and data-driven decision systems. He currently serves as a Corporate Vice President, AI & Data at New York Life and previously held leadership roles at Amazon, where he worked for 8+ years across product management, operations, and finance. At Amazon, Srinivas led enterprise-scale optimization initiatives in transportation and fulfillment, delivering hundreds of millions of dollars in annual cost savings through advanced analytics, automation, and data-driven process redesign. His work included mentoring product and analytics teams, defining KPI-driven operating mechanisms, and evaluating ROI for large technology investments. His background uniquely blends deep quantitative analysis, enterprise technology deployment, and people leadership. Srinivas is a Senior Member of IEEE and a member of the Forbes Technology Council, reflecting his professional standing and contributions to technology leadership. Srinivas is also an active contributor to the research community, serving as a reviewer for the IEEE Internet of Things Journal and multiple IEEE international conferences. His academic foundation includes an MBA from Duke University's Fuqua School of Business, and a Bachelor's degree in Engineering from IIT Bombay, where he also published an international journal paper in neural networks.

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• Computers & TechnologyComputer ScienceArtificial IntelligenceGenerative AI

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• Print Length: 252 Pages
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