Snowflake Recipes : A Problem-Solution Approach to Implementing Modern Data Pipelines / by Dillon Dayton, John Eipe.

Format:

Book

Author/Creator:

Dayton, Dillon.

Contributor:

Eipe, John.

Series:

Professional and Applied Computing Series

Language:

English

Subjects (All):

Cloud computing.

Python (Computer program language).

Machine learning.

Cloud Computing.

Python.

Machine Learning.

Local Subjects:

Cloud Computing.

Python.

Machine Learning.

Physical Description:

1 online resource (413 pages)

Edition:

1st ed. 2024.

Place of Publication:

Berkeley, CA : Apress : Imprint: Apress, 2024.

Summary:

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.

Contents:

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.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9798868809385

OCLC:

1481901449