The Ultimate Guide to Snowpark: Design and deploy Snowflake Snowpark with Python for efficient data workloads

Develop robust data pipelines, deploy mature machine learning models, and build secure data apps with Snowflake Snowpark using Python

Key Features

• Get to grips with Snowflake 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 Snowflake 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

1. Discovering Snowpark
2. Establishing a Foundation with Snowpark
3. Simplifying Data Processing Using Snowpark
4. Building Data Engineering Pipelines with Snowpark
5. Developing Data Science Projects with Snowpark
6. Deploying and Managing ML Models with Snowpark
7. Developing a Native Application with Snowpark
8. Introduction to Snowpark Container Services

Shankar Narayanan is a Technical Architect with over a decade of diverse experience leading and delivering large-scale Data and Cloud implementations for Fortune 500 companies across various industries. He has successfully implemented Snowflake Data Cloud for many organizations leading the customers to adopt Snowflake. He holds a bachelor's and master's degree in Computer science and holds many certifications in multi-cloud platforms and Snowflake. He is an award-winning blogger and actively contributes to various technical publications and open-source projects. For his technical contribution to the community, He has been selected as SAP Community Topic leader by SAP and is selected as one of the 72 Snowflake Data Heroes by Snowflake.

Vivekanandan spearheads the GenAI enablement team at Verizon, leveraging over a decade of expertise in Data Science and Big Data. His professional journey spans across building analytics solutions and products across diverse domains, and proficient in cloud analytics and data warehouses. He holds a bachelor's degree in Industrial engineering from Anna University, a long distance program in Big Data analytics from IIM, Bangalore, and a master's in Data Science from Eastern University. As a seasoned trainer, he imparts his knowledge, specializing in Snowflake and GenAI, also a data science guest faculty and advisor for various educational institutes. His solution is ranked in the top 1 percentile in Kaggle Kernels globally.