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Big Data in Action: The Modern Blueprint for Building Data Mesh, Lakehouses, and Scalable AI Systems
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Publisher: Independently Published
Published: Jan 13 2026
Pages: 162
Weight: 0.64
Height: 0.35 Width: 7.00 Depth: 10.00
Language: English
Big Data in Action: The Modern Blueprint for Building Data Mesh, Lakehouses, and Scalable AI Systems
Your data stack is growing, but your results are not. Pipelines sprawl across teams, costs creep upward, dashboards disagree, and every new AI initiative feels harder than the last. You have the tools, Spark, cloud warehouses, streaming platforms, vector stores, but no unifying blueprint that turns complexity into leverage. This book starts where most big data strategies break down and shows how modern architectures actually work in practice.
Big Data in Action presents a clear, execution-focused framework for designing and operating data platforms that scale with both the organization and its ambitions. It connects data mesh thinking, lakehouse architectures, and AI-ready systems into a single, coherent model. Rather than abstract theory, the book focuses on real architectural decisions, trade-offs, and patterns that engineering teams face when building platforms for analytics, machine learning, and production AI.
You will see how decentralized ownership, shared infrastructure, and standardized data products come together to reduce friction instead of adding it. You will understand how lakehouses replace fragile pipelines with durable data foundations, and how those foundations power modern AI workloads, from batch training to real-time inference. Each concept is grounded in practical system design, helping you reason about scale, reliability, governance, and cost without slowing teams down.
What you'll gain from this book:
A practical mental model for designing data mesh architectures that work at scale
Clear guidance on building lakehouses that support analytics, streaming, and AI together
Proven patterns for integrating big data platforms with modern AI systems
Insight into operational concerns such as reliability, observability, and cost control
A decision-making framework for choosing technologies based on constraints, not trends
If you are a data engineer, platform architect, analytics leader, or AI practitioner who wants fewer firefights and more forward momentum, this book gives you the blueprint you've been missing. Build systems that scale, teams that move faster, and data platforms that finally deliver on their promise.
Get your copy of Big Data in Action and start building big data systems that actually work.
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