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Название: Snowflake Recipes: A Problem-Solution Approach to Implementing Modern Data Pipelines
Автор: Dillon Dayton, John Eipe
Издательство: Apress
Год: 2024
Страниц: 401
Язык: английский
Формат: pdf
Размер: 37.1 MB
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. 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.
Автор: Dillon Dayton, John Eipe
Издательство: Apress
Год: 2024
Страниц: 401
Язык: английский
Формат: pdf
Размер: 37.1 MB
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. 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.