What do you think?
Rate this book
Snowflake Data Engineering
A practical introduction to data engineering on the powerful Snowflake cloud data platform.
Data engineers create the pipelines that ingest raw data, transform it, and funnel it to the analysts and professionals who need it. The Snowflake cloud data platform provides a suite of productivity-focused tools and features that simplify building and maintaining data pipelines. In Snowflake Data Engineering, Snowflake Data Superhero Maja Ferle shows you how to get started.
In Snowflake Data Engineering you will learn how
• Ingest data into Snowflake from both cloud and local file systems
• Transform data using functions, stored procedures, and SQL
• Orchestrate data pipelines with streams and tasks, and monitor their execution
• Use Snowpark to run Python code in your pipelines
• Deploy Snowflake objects and code using continuous integration principles
• Optimize performance and costs when ingesting data into Snowflake
Snowflake Data Engineering reveals how Snowflake makes it easy to work with unstructured data, set up continuous ingestion with Snowpipe, and keep your data safe and secure with best-in-class data governance features. Along the way, you’ll practice the most important data engineering tasks as you work through relevant hands-on examples. Throughout, author Maja Ferle shares design tips drawn from her years of experience to ensure your pipeline follows the best practices of software engineering, security, and data governance.
Foreword by Joe Reis.
About the technology
Pipelines that ingest and transform raw data are the lifeblood of business analytics, and data engineers rely on Snowflake to help them deliver those pipelines efficiently. Snowflake is a full-service cloud-based platform that handles everything from near-infinite storage, fast elastic compute services, inbuilt AI/ML capabilities like vector search, text-to-SQL, code generation, and more. This book gives you what you need to create effective data pipelines on the Snowflake platform.
About the book
Snowflake Data Engineering guides you skill-by-skill through accomplishing on-the-job data engineering tasks using Snowflake. You’ll start by building your first simple pipeline and then expand it by adding increasingly powerful features, including data governance and security, adding CI/CD into your pipelines, and even augmenting data with generative AI. You’ll be amazed how far you can go in just a few short chapters!
What's inside
• Ingest data from the cloud, APIs, or Snowflake Marketplace
• Orchestrate data pipelines with streams and tasks
• Optimize performance and cost
About the reader
For software developers and data analysts. Readers should know the basics of SQL and the Cloud.
About the author
Maja Ferle is a Snowflake Subject Matter Expert and a Snowflake Data Superhero who holds the SnowPro Advanced Data Engineer and the SnowPro Advanced Data Analyst certifications.
Table of Contents
Part 1
1 Data engineering with Snowflake
2 Creating your first data pipeline
Part 2
3 Best practices for data staging
4 Transforming data
5 Continuous data ingestion
6 Executi
Data engineers create the pipelines that ingest raw data, transform it, and funnel it to the analysts and professionals who need it. The Snowflake cloud data platform provides a suite of productivity-focused tools and features that simplify building and maintaining data pipelines. In Snowflake Data Engineering, Snowflake Data Superhero Maja Ferle shows you how to get started.
In Snowflake Data Engineering you will learn how
• Ingest data into Snowflake from both cloud and local file systems
• Transform data using functions, stored procedures, and SQL
• Orchestrate data pipelines with streams and tasks, and monitor their execution
• Use Snowpark to run Python code in your pipelines
• Deploy Snowflake objects and code using continuous integration principles
• Optimize performance and costs when ingesting data into Snowflake
Snowflake Data Engineering reveals how Snowflake makes it easy to work with unstructured data, set up continuous ingestion with Snowpipe, and keep your data safe and secure with best-in-class data governance features. Along the way, you’ll practice the most important data engineering tasks as you work through relevant hands-on examples. Throughout, author Maja Ferle shares design tips drawn from her years of experience to ensure your pipeline follows the best practices of software engineering, security, and data governance.
Foreword by Joe Reis.
About the technology
Pipelines that ingest and transform raw data are the lifeblood of business analytics, and data engineers rely on Snowflake to help them deliver those pipelines efficiently. Snowflake is a full-service cloud-based platform that handles everything from near-infinite storage, fast elastic compute services, inbuilt AI/ML capabilities like vector search, text-to-SQL, code generation, and more. This book gives you what you need to create effective data pipelines on the Snowflake platform.
About the book
Snowflake Data Engineering guides you skill-by-skill through accomplishing on-the-job data engineering tasks using Snowflake. You’ll start by building your first simple pipeline and then expand it by adding increasingly powerful features, including data governance and security, adding CI/CD into your pipelines, and even augmenting data with generative AI. You’ll be amazed how far you can go in just a few short chapters!
What's inside
• Ingest data from the cloud, APIs, or Snowflake Marketplace
• Orchestrate data pipelines with streams and tasks
• Optimize performance and cost
About the reader
For software developers and data analysts. Readers should know the basics of SQL and the Cloud.
About the author
Maja Ferle is a Snowflake Subject Matter Expert and a Snowflake Data Superhero who holds the SnowPro Advanced Data Engineer and the SnowPro Advanced Data Analyst certifications.
Table of Contents
Part 1
1 Data engineering with Snowflake
2 Creating your first data pipeline
Part 2
3 Best practices for data staging
4 Transforming data
5 Continuous data ingestion
6 Executi
368 pages, Paperback
Published January 28, 2025
2 people are currently reading
15 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 5 of 5 reviews
February 5, 2025
Snowflake Data Engineering is a solid, hands-on guide for mastering Snowflake’s data engineering capabilities. It breaks down complex topics like data ingestion, transformation, and automation in an easy-to-follow way. The book covers cool features like Snowpipe, Snowpark, and even Generative AI, keeping things fresh and relevant. Real-world examples and step-by-step tutorials make it great for both beginners and experienced pros. It also dives into cost management, security, and performance tuning—super useful for anyone working with Snowflake at scale. The writing is clear, engaging, and avoids unnecessary fluff. If you're serious about Snowflake and want to level up your skills, this book is a must-read!
February 13, 2025
The book is very interesting to learn up to date snowflake features as it covers mostly all functionalities available in snowflake, even the newest ones, including public preview.
The book is also well written, with clear explanations, and it is very interesting that all chapters follown an example of a fictional business doing in practice what you study in each chapter. This makes the book more engaging itself and provides an opportunity to learn by doing.
All in all a very recommende dbook for the ones interested in knowing how to perform dana engineering in snowflake and even for the ones like me that already know snowflake because you will learn more stuff as well.
Disclaimer: I've read the book as part of the MEAP program at Manning and submitted my own opinion along.
The book is also well written, with clear explanations, and it is very interesting that all chapters follown an example of a fictional business doing in practice what you study in each chapter. This makes the book more engaging itself and provides an opportunity to learn by doing.
All in all a very recommende dbook for the ones interested in knowing how to perform dana engineering in snowflake and even for the ones like me that already know snowflake because you will learn more stuff as well.
Disclaimer: I've read the book as part of the MEAP program at Manning and submitted my own opinion along.
January 28, 2025
This is a really comprehensive book on tools, techniques and best practices on Snowflake data engineering. I highly recommend it to everyone doing or learning data "wrangling". I would even make it a mandatory read before taking Snowflake certification exams.
Read
February 9, 2025Maja Ferle has provided an excellent Data Engineering example which is expanded on in each chapter of her book. You are also guaranteed to learn valuable insight from the discussion of several newer Snowflake features and it will greatly assist in increasing your productivity!
February 4, 2025
Complete end2end guide for Snowflake DataEngineering !!
Displaying 1 - 5 of 5 reviews