Book Image

Data Modeling with Snowflake

By : Serge Gershkovich
5 (2)
Book Image

Data Modeling with Snowflake

5 (2)
By: Serge Gershkovich

Overview of this book

The Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before. Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that’s easily accessible to everyone in the organization. This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before – giving you a two-for-one crash course in theory as well as direct application. By the end of this Snowflake book, you’ll have learned how to leverage Snowflake’s innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.
Table of Contents (24 chapters)
1
Part 1: Core Concepts in Data Modeling and Snowflake Architecture
8
Part 2: Applied Modeling from Idea to Deployment
14
Part 3: Solving Real-World Problems with Transformational Modeling

Tasks

Snowflake uses tasks to schedule and automate data loading and transformation. Although data movement is not tracked in relational modeling, it is an integral part of transformational modeling and is covered here for completeness.

Tasks automate data pipelines by executing SQL in serial or parallel steps. Tasks can be combined with streams for continuous ELT workflows to process recently changed table rows. This can be done serverlessly (using auto-scalable Snowflake-managed compute clusters that do not require an active warehouse) or using a dedicated user-defined warehouse.

The code for creating a task is as follows:

CREATE TASK <task_name>
...
[ AFTER <parent_task_1> [ , <parent_task_2> , ... ] ]
[ WHEN <boolean_expr> ]
AS <sql>

Tasks are simple to understand—they run a SQL command (or execute a stored procedure) on a schedule or when called as part of a parent task. The following figure shows how tasks can be chained serially...