Snowflake Cookbook : Strategic and Practical Recipes for Building Governed, Intelligent, AI-Ready Data Platforms.

Format:

Book

Author/Creator:

Belanger, Keith.

Contributor:

Belanger, Keith

Qureshi, Hamid Mahmood

Sharif, Hammad

Graziano, Kent

Language:

English

Subjects (All):

Data warehousing.

Artificial intelligence.

Physical Description:

1 online resource (458 pages)

Edition:

1st ed.

Place of Publication:

Birmingham : Packt Publishing, Limited, 2026.

Summary:

Build modern data and AI platforms in the Snowflake AI Data Cloud with practical recipes for data governance, automation, Cortex AI, observability, and intelligent application development.

Contents:

Intro

Snowflake Cookbook

Cover

Copyright and Credits

Foreword

Contributors

About the author

About the reviewers

Table of Contents

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Get the code bundle

Conventions used

Free benefits with your book

How to unlock

Get in touch

Share your thoughts

Chapter 1: Getting Started with Snowflake

Technical requirements

Creating a new Snowflake account

Getting ready

How to do it…

How it works…

Using Snowsight and creating a tailored multi-cluster virtual warehouse

There's more…

Using Snowsight and executing a query

Using SnowSQL to connect to Snowflake

Connecting to Snowflake with JDBC

Creating a new account admin user and understanding built-in roles

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Chapter 2: Managing the Data Life Cycle

Managing a database

Managing a schema

Managing tables

Managing external tables and stages

Managing views in Snowflake

Integrating Snowflake with Git

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Chapter 3: Loading and Extracting Data Into and Out of Snowflake

Preparing stage for data loading

Loading delimited bulk data into Snowflake from cloud storage

Loading delimited bulk data into Snowflake from your local machine

Loading Parquet files into Snowflake

Transforming JSON data into relational tables in Snowflake

Processing newline-delimited JSON (NDJSON) into a Snowflake table

Processing near-real-time data into a Snowflake table using Snowpipe

Extracting data from Snowflake into internal and external stages

Building data ingestion pipelines with Snowflake Openflow

Chapter 4: Building Data Pipelines in Snowflake

Creating and scheduling a task

Connecting pipelines through a task tree

Querying and viewing task history

Exploring the concept of streams to capture table-level changes

Combining the concepts of streams and tasks to build pipelines that process changed data on a schedule

Converting data types and Snowflake's failure management

How it works….

There's more…

Managing context using different utility functions

Using Dynamic Tables for data lifecycle automation

Chapter 5: Data Protection and Security in Snowflake

Setting up custom roles and completing the role hierarchy

Configuring and assigning a default role to a user

Delineating user management from security and role management

Configuring custom roles for managing access to highly secure data

Setting up development, testing, pre-production, and production database hierarchies and roles

Safeguarding the ACCOUNTADMIN role and users in the ACCOUNTADMIN role

Implementing column-level security with masking policies

Implementing row-level security with row access policies

Classifying and tagging sensitive data

Chapter 6: Performance and Cost Optimization

Examining table schemas and deriving an optimal structure for a table

Identifying query plans and bottlenecks

Weeding out inefficient queries through analysis

Getting ready.

How to do it…

Identifying and reducing unnecessary Fail-safe and Time Travel storage usage

Projections in Snowflake for performance

Reviewing query plans to modify table clustering

Optimizing virtual warehouse scale

Optimizing warehouse generations and Query Acceleration Service (QAS)

Chapter 7: Secure Data Sharing

Sharing a table with another Snowflake account

Sharing data through a view with another Snowflake account

Sharing a complete database with another Snowflake account and future objects

Creating reader accounts and configuring them for non-Snowflake sharing

Sharing an object with a non-Snowflake user

Keeping costs in check when sharing data with non-Snowflake users

Publishing a data share to the Snowflake Internal Marketplace

Chapter 8: Back to the Future with Time Travel

Using Time Travel to return to the state of data at a particular time

Using Time Travel to recover from the accidental loss of table data

How to do it….

How it works…

Identifying dropped databases, tables, and other objects and restoring them using Time Travel

Using Time Travel in conjunction with cloning to improve debugging

Using cloning to set up new environments based on the production environment rapidly

Managing Time Travel and cloning retention policies for governance

Chapter 9: Advanced SQL Techniques

Managing timestamp data

Extracting calendar intelligence from date and time data

Performing unique counts and approximate distinct analysis

Managing transactions in Snowflake

Ordered analytics over window frames

Generating sequences in Snowflake

Using QUALIFY to simplify filtering of window functions

Creating and using user-defined data types

Chapter 10: Extending Snowflake Capabilities

Creating a scalar user-defined function using SQL

How to do it...

How it works...

Creating a table user-defined function using SQL

How to do it

How it works

Creating a scalar user-defined function using JavaScript

How it works.

Creating a table user-defined function using JavaScript.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Other Format:

Print version: Belanger, Keith Snowflake Cookbook

ISBN:

9781806384761

OCLC:

1605656461