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173492099
Data Modeling with Snowflake: A practical guide to accelerating Snowflake development using universal modeling techniques 2nd ed. Edition
Nº de artículo:
173492099
PAB 66
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This edition expands beyond data modeling to explore KPIs in project management, offering readers a practical playbook for promoting data modeling within their organizations.
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What Stands Out
Universal Modeling Techniques
Leverages universal modeling techniques to streamline Snowflake development, enabling users to accelerate their data modeling processes efficiently across varied datasets and architectures.
Practical Insights
Offers practical guidance through real-world scenarios and examples, enhancing the learning experience and ensuring users can apply the techniques effectively in everyday development tasks.
Updated 2nd Edition
The second edition includes the latest advancements in Snowflake, ensuring that readers access cutting-edge information and practices essential for optimizing their data management strategies.
Detalles de producto
| Publisher | Packt Publishing |
| Publication date | September 2, 2025 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 444 pages |
| ISBN-10 | 1837028036 |
| ISBN-13 | 978-1837028030 |
| Item Weight | 1.63 pounds (740 grams) |
| Dimensions | 7.5 x 1 x 9.25 inches (19.1 x 2.5 x 23.5 cm) |
Who Should Buy?
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Data Analysts
Ideal for data analysts seeking to enhance their skills in using Snowflake for data modeling and analysis.
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Database Developers
Useful for database developers wanting practical techniques for efficient Snowflake development and modeling practices.
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BI Professionals
Perfect for business intelligence professionals looking to improve their data management and visualization skills using Snowflake.
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Beginners
Not suitable for beginners unfamiliar with data modeling concepts, as it assumes prior knowledge and experience.
DESCRIPCIÓN DEL PRODUCTO
Data Modeling with Snowflake: A practical guide to accelerating Snowflake development using universal modeling techniques 2nd ed. Edition
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Data Modeling & Design Editorial Review
**Editorial Review** "Data Modeling with Snowflake: A Practical Guide to Accelerating Snowflake Development Using Universal Modeling Techniques," authored by Serge Gershkovich, stands as an essential resource for engineers and data architects delving into Snowflake data warehouses. This second edition goes beyond the fundamentals of how to operate Snowflake and focuses on the underlying principles of good data modeling, emphasizing its significance in terms of performance, cost management, and maintainability. Readers appreciate the book's practical approach, which utilizes universal modeling techniques alongside real-world examples and SQL recipes, demonstrating effective data organization in Snowflake to optimize query performance. The author's clear explanations of Snowflake's native features, including micro-partitions, clustering, and materialized views, offer valuable insights on when and how to deploy these tools, steering clear of unnecessary complexities. The book resonates particularly well with professionals seeking to standardize data modeling within their teams, bridging the gap between business terminology and technical architecture. It addresses common pitfalls in data modeling, teaching practitioners to avoid designs that could inflate operational costs or slow down processing times, while illustrating the concept that proper modeling is about establishing clarity, trust, and scalability. The structured layout of the book, progressing from core principles to advanced modeling strategies and real-world solutions, makes it accessible even to those less familiar with Snowflake. Comprehensive sections on data normalization, naming conventions, and enterprise-level strategies add substantial value, making it a great reference for addressing both theoretical and operational challenges. While the text may be dense at 445 pages, the wealth of information and practical insights gleaned from it can significantly impact both individual projects and overall data strategy within organizations. Overall, Gershkovich's blend of depth and applicability positions this book as a vital tool for anyone serious about leveraging Snowflake for modern data management. **
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ventajas
- Comprehensive coverage of universal modeling techniques.
- Practical examples and SQL recipes enhance usability.
- Strong focus on cost control and query performance.
- Bridges the gap between business needs and technical architecture.
- Clear explanations of Snowflake's native features.
- In-depth discussions of data normalization and naming conventions.
- Provides insights on enterprise-level data strategy.
Contras
- Lengthy at 445 pages; may feel overwhelming for some.
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características y beneficios
- Uncover new database objects like Iceberg and Dynamic Tables in Snowflake.
- Learn about the evolving landscape of data management with AI-enabled analytics.
- Gain practical strategies for implementing new tools in real-world settings.
- Explore effective methods for aligning business and data teams.
- Enhance your ability to win support for budget proposals backed by business metrics.
- Emphasizes the necessity of solid data modeling for successful AI outcomes.
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