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SKU/Artículo: AMZ-B0GKPBCKPW
From Data Analyst to Analytics Engineer: Master Modular SQL, Build Scalable Data Pipelines, and Automate Workflows using dbt and Snowflake.
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.75 kg
0.75 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Stop writing ad-hoc queries and start building scalable data systems. From Data Analyst to Analytics Engineer is your definitive guide to mastering the modern data stack—Snowflake, dbt, and AI—and making the leap from analyst to engineer in 2026.Book SummaryThis comprehensive guide bridges the gap between traditional data analysis and analytics engineering. It moves beyond simple SQL to teach you how to treat data transformations as production software. You will learn to architect robust dependency graphs (DAGs), implement CI/CD pipelines with Snowflake Native Git, and enforce data quality through automated testing and "circuit breaker" systems.The book dives deep into the 2026 analytics landscape, integrating Python (Snowpark) and AI-driven analytics (Snowflake Cortex) directly into your workflows. Through hands-on projects—such as building a "Customers 360" data mart, optimizing slow queries for 50% cost savings, and deploying an internal "AI Analyst"—you will gain the practical skills to build resilient, self-documenting data platforms that drive business value.Key Features & BenefitsMaster the 2026 Stack: Deep dives into Snowflake, dbt Core/Cloud, and Snowflake Cortex for AI-driven workflows.Production-Grade Engineering: Learn "Thinking in DAGs," modular SQL design, and how to implement rigorous CI/CD and automated testing.Advanced Optimization: Techniques to reduce Snowflake costs and speed up queries by 10x using Dynamic Tables, caching, and incremental loading.AI & Python Integration: Build "AI Analysts" with LLMs and perform complex data transformations using Snowpark and Pandas inside Snowflake.Hands-On Projects: Includes real-world capstones like refactoring "spaghetti SQL" and deploying near real-time streaming pipelines.Author BioMonroe Easterman is a data expert dedicated to modern analytics engineering, helping professionals transition from performing ad-hoc analysis to architecting scalable, automated, and reliable data systems.Future-proof your data career today—grab your copy and start building analytics systems that last!
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