Develop robust data pipelines, deploy mature machine learning models, and build secure data apps with Snowpark using Python
Key Features
- Get to grips with Snowpark's basic and advanced features
- Implement workloads in domains like data engineering, data science, and data applications using Snowpark with Python
- Deploy Snowpark in production with practical examples and best practices
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Snowpark is a powerful framework that helps you unlock numerous possibilities within the Snowflake Data Cloud. However, without proper guidance, leveraging the full potential of Snowpark with Python can be challenging. Packed with practical examples and code snippets, this book will be your go-to guide to using Snowpark with Python successfully.
The Ultimate Guide to Snowpark helps you develop an understanding of Snowpark and how it enables you to implement workloads in data engineering, data science, and data applications within the Data Cloud. From configuration and coding styles to workloads such as data manipulation, collection, preparation, transformation, aggregation, and analysis, this guide will equip you with the right knowledge to make the most of this framework. You'll discover how to build, test, and deploy data pipelines and data science models. As you progress, you'll deploy data applications natively in Snowflake and operate large language models (LLMs) using Snowpark container services.
By the end of this book, you'll be able to leverage Snowpark's capabilities and propel your career as a Snowflake developer to new heights.
What you will learn
- Harness Snowpark with Python for diverse workloads
- Develop robust data pipelines with Snowpark using Python
- Deploy mature machine learning models
- Explore the process of developing, deploying, and monetizing native apps using Snowpark
- Deploy and operate containers in Snowpark
- Discover the pathway to adopting Snowpark effectively in production
Who this book is for
This book is for data engineers, data scientists, developers, and data practitioners seeking an in-depth understanding of Snowpark's features and best practices for deploying various workloads in Snowpark using the Python programming language. Basic knowledge of SQL, proficiency in Python, an understanding of data engineering and data science basics, and familiarity with the Snowflake Data Cloud platform are required to get the most out of this book.
Table of Contents
- Discovering Snowpark
- Establishing a Foundation with Snowpark
- Simplifying Data Processing Using Snowpark
- Building Data Engineering Pipelines with Snowpark
- Developing Data Science Projects with Snowpark
- Deploying and Managing ML Models with Snowpark
- Developing a Native Application with Snowpark
- Introduction to Snowpark Container Services