Additional information
by Dillon Dayton (Author), John Eipe (Author)
Explore Snowflake's core concepts and unique features that differentiates it from industry competitors, such as, Azure Synapse and Google BigQuery. This book provides recipes for architecting and developing modern data pipelines on the Snowflake data platform by employing progressive techniques, agile practices, and repeatable strategies.
You'll walk through step-by-step instructions on ready-to-use recipes covering a wide range of the latest development topics. Then build scalable development pipelines and solve specific scenarios common to all modern data platforms, such as, data masking, object tagging, data monetization, and security best practices. Throughout the book you'll work with code samples for Amazon Web Services, Microsoft Azure, and Google Cloud Platform. There's also a chapter devoted to solving machine learning problems with Snowflake.
Authors Dillon Dayton and John Eipe are both Snowflake SnowPro Core certified, specializing in data and digital services, and understand the challenges of finding the right solution to complex problems. The recipes in this book are based on real world use cases and examples designed to help you provide quality, performant, and secured data to solve business initiatives.
What You'll Learn
- Handle structured and un- structured data in Snowflake.
- Apply best practices and different options for data transformation.
- Understand data application development.
- Implement data sharing, data governance and security.
Who This book Is For
Data engineers, scientists and analysts moving into Snowflake, looking to build data apps. This book expects basic knowledge in Cloud (AWS or Azure or GCP), SQL and Python
Back Jacket
Explore Snowflake's core concepts and unique features that differentiates it from industry competitors, such as, Azure Synapse and Google BigQuery. This book provides recipes for architecting and developing modern data pipelines on the Snowflake data platform by employing progressive techniques, agile practices, and repeatable strategies.
You'll walk through step-by-step instructions on ready-to-use recipes covering a wide range of the latest development topics. Then build scalable development pipelines and solve specific scenarios common to all modern data platforms, such as, data masking, object tagging, data monetization, and security best practices. Throughout the book you'll work with code samples for Amazon Web Services, Microsoft Azure, and Google Cloud Platform. There's also a chapter devoted to solving machine learning problems with Snowflake.
Authors Dillon Dayton and John Eipe are both Snowflake SnowPro Core certified, specializing in data and digital services, and understand the challenges of finding the right solution to complex problems. The recipes in this book are based on real world use cases and examples designed to help you provide quality, performant, and secured data to solve business initiatives.
You will:
- Handle structured and un- structured data in Snowflake.
- Apply best practices and different options for data transformation.
- Understand data application development.
- Implement data sharing, data governance and security.
Author Biography
Dillon Dayton is a senior consultant for CDW. Over the last 10 years he has performed in a data engineering and architect role with numerous companies across a slew of industries including healthcare, retail, and finance. Dillon is Snowflake SnowPro Core certified and participates in the Snowflake SME program. In his spare time, he enjoys applying his data and engineering background to hobbies like motorsports, gardening, and fishing.
John Eipe is a Senior Solutions Specialist for CDW and has over 10 years of experience in various roles from enterprise application development to data engineering. He worked primarily with customers from the ecommerce and insurance domain. John is Snowflake SnowPro Core certified and has been working extensively on Snowflake in the recent years. Apart from work, he enjoys cooking and time with his kids.
