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SKU/Artículo: AMZ-B0FX3CDF3X
Data Architecture with Snowflake: Design and Build Scalable Cloud Data Systems for Analytics, AI, and Modern Enterprises
Format:
Kindle
Detalles del producto
Disponibilidad:
Fuera de stock
Fuera de stock
Peso con empaque:
0.36 kg
0.36 kg
Devolución:
No
No
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Data Architecture with Snowflake: Design and Build Scalable Cloud Data Systems for Analytics, AI, and Modern Enterprises Modern businesses run on data—and the ability to store, manage, and analyze that data efficiently defines their success. Data Architecture with Snowflake is a complete, hands-on guide to designing and implementing scalable cloud data systems using the Snowflake Data Cloud. Whether you’re a data engineer, architect, analyst, or technology leader, this book equips you with the knowledge and practical skills to turn raw data into actionable intelligence at enterprise scale. Written in a clear, conversational style, the book bridges foundational theory with real-world engineering practice. It begins by explaining the evolution of data architecture—from legacy on-premise systems to modern cloud-native environments—and then introduces Snowflake’s groundbreaking design: the separation of compute, storage, and services. Through step-by-step exploration, you’ll understand how Snowflake’s multi-cluster shared data architecture delivers performance, concurrency, and elasticity unmatched by traditional systems. You’ll learn how to build efficient data models, design ETL and ELT pipelines, and optimize performance for complex analytics workloads. The book demonstrates how to integrate Snowflake with tools like dbt, Airflow, and Power BI, and how to extend its capabilities with Snowpark and Python for advanced data science and AI use cases. Each chapter is grounded in real-world examples—from retail analytics and financial reporting to global data sharing and multi-cloud deployment—so you can apply the concepts directly to your organization’s data strategy. Beyond the technical aspects, Data Architecture with Snowflake dives deep into governance, security, and cost management, teaching you how to protect sensitive information, enforce compliance, and optimize compute credits effectively. You’ll also explore emerging architectural patterns such as data mesh, data fabric, and AI-native pipelines that are shaping the future of enterprise data platforms. By the end of this book, you’ll have a comprehensive understanding of how to design, build, and maintain modern data systems that are fast, reliable, and ready for the next generation of analytics and artificial intelligence. Key Highlights: Master Snowflake’s architecture and its advantages over traditional data warehouses. Learn how to model, load, transform, and query massive datasets efficiently. Integrate Snowflake with modern data tools and machine learning frameworks. Implement robust governance, security, and cost optimization strategies. Explore real-world design patterns and enterprise-level implementation case studies. Who This Book Is For: This book is ideal for data engineers, architects, BI developers, and analytics professionals who want to master Snowflake as a central component of their data ecosystem. It’s also valuable for IT leaders and decision-makers seeking to modernize legacy data infrastructures and harness the full potential of the cloud for analytics and AI. If you’re ready to transform how your organization handles data—moving from fragmented, slow systems to a unified, scalable, and intelligent cloud platform—this is the book you’ve been waiting for. Equip yourself with the strategies and techniques used by modern enterprises worldwide. Learn to build data architectures that don’t just store information but fuel insights, innovation, and growth. Take control of your data future today—start your journey toward mastering modern data architecture with Snowflake.
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