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Snowflake recipesa problem-solution ...
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Dayton, Dillon.
Snowflake recipesa problem-solution approach to implementing modern data pipelines /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Snowflake recipesby Dillon Dayton, John Eipe.
Reminder of title:
a problem-solution approach to implementing modern data pipelines /
Author:
Dayton, Dillon.
other author:
Eipe, John.
Published:
Berkeley, CA :Apress :2024.
Description:
xvi, 404 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Cloud computing.
Online resource:
https://doi.org/10.1007/979-8-8688-0938-5
ISBN:
9798868809385$q(electronic bk.)
Snowflake recipesa problem-solution approach to implementing modern data pipelines /
Dayton, Dillon.
Snowflake recipes
a problem-solution approach to implementing modern data pipelines /[electronic resource] :by Dillon Dayton, John Eipe. - Berkeley, CA :Apress :2024. - xvi, 404 p. :ill. (some col.), digital ;24 cm.
Chapter 1: Introduction to Snowflake -- Chapter 2: Bringing Your Data into Snowflake -- Chapter 3: Handling Atypical Data -- Chapter 4: Data Security and Privacy -- Chapter 5: Handling Near and Real Time Data -- Chapter 6: Programmable Data Pipelines -- Chapter 7: Data Reusability and Monetization -- Chapter 8: Data Recovery and Protection -- Chapter 9: Applications Integration -- Chapter 10: Machine Learning.
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.
ISBN: 9798868809385$q(electronic bk.)
Standard No.: 10.1007/979-8-8688-0938-5doiSubjects--Uniform Titles:
Snowflake (Electronic resource)
Subjects--Topical Terms:
378527
Cloud computing.
LC Class. No.: QA76.585 / .D39 2024
Dewey Class. No.: 004.6782
Snowflake recipesa problem-solution approach to implementing modern data pipelines /
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a problem-solution approach to implementing modern data pipelines /
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by Dillon Dayton, John Eipe.
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Chapter 1: Introduction to Snowflake -- Chapter 2: Bringing Your Data into Snowflake -- Chapter 3: Handling Atypical Data -- Chapter 4: Data Security and Privacy -- Chapter 5: Handling Near and Real Time Data -- Chapter 6: Programmable Data Pipelines -- Chapter 7: Data Reusability and Monetization -- Chapter 8: Data Recovery and Protection -- Chapter 9: Applications Integration -- Chapter 10: Machine Learning.
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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.
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based on 0 review(s)
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