Advanced Snowflake: Processing Data, Developing Applications, and Deploying ML Models at Scale

by Muhammad Fasih Ullah

Overview

As Snowflake's capabilities expand, staying updated with its latest features and functionalities can be overwhelming for users. The platform's rapid development introduces advanced tools like Snowpark and the Native App Framework, which are crucial for optimizing data operations but may seem complex to navigate without a structured framework.

In this essential book, author Muhammad Fasih Ullah offers a detailed guide to understanding these sophisticated tools, ensuring you can leverage the full potential of Snowflake for data processing, application development, and deploying machine learning models at scale. You'll gain actionable insights and structured examples to transform your understanding and skills in handling advanced data scenarios within Snowflake. By the end of this book, you will:

• Grasp advanced features such as Snowpark, Snowflake App Framework, and Iceberg tables
• Enhance your projects with geospatial functions for comprehensive geospatial analytics
• Interact with Snowflake using a variety of programming languages through Snowpark
• Implement and manage machine learning models effectively using Snowpark ML
• Develop and deploy applications within the Snowflake environment

Product Details

ISBN-13:	9781098170219
Publisher:	O'Reilly Media, Incorporated
Publication date:	12/02/2025
Pages:	250
Product dimensions:	7.00(w) x 9.19(h) x 0.00(d)

About the Author

Muhammad Fasih Ullah is the Head of Data and Analytics for Youty Group AB. His current work revolves around developing resilient and high-functioning data organizations responsible for managing scalable data and analytics needs. He has also helped teams design and build scalable data layers that process millions of rows in a day and prepare data for analytical use. As a 2x Snowflake Data Superhero, Muhammad has used his in-depth knowledge of Snowflake to help save his organizations and clients hundreds of thousands of dollars in data warehousing costs.