Snowflake Cookbook: Techniques for building modern cloud data warehousing solutions
by Hamid Mahmood Qureshi and Hammad Sharif
Publisher finelybook 出版社: Packt Publishing (February 25,2021)
Language 语言: English
Print Length 页数: 330 pages
ISBN-10: 1800560613
ISBN-13: 9781800560611
Book Description
Develop modern solutions with Snowflake’s unique architecture and integration capabilities; process bulk and real-time data into a data lake; and leverage time travel,cloning,and data-sharing features to optimize data operations
Snowflake is a unique cloud-based data warehousing platform built from scratch to perform data management on the cloud. This book introduces you to Snowflake’s unique architecture,which places it at the forefront of cloud data warehouses.
You’ll explore the compute model available with Snowflake,and find out how Snowflake allows extensive scaling through the virtual warehouses. You will then learn how to configure a virtual warehouse for optimizing cost and performance. Moving on,you’ll get to grips with the data ecosystem and discover how Snowflake integrates with other technologies for staging and loading data.
As you progress through the chapters,you will leverage Snowflake’s capabilities to process a series of SQL statements using tasks to build data pipelines and find out how you can create modern data solutions and pipelines designed to provide high performance and scalability. You will also get to grips with creating role hierarchies,adding custom roles,and setting default roles for users before covering advanced topics such as data sharing,cloning,and performance optimization.
By the end of this Snowflake book,you will be well-versed in Snowflake’s architecture for building modern analytical solutions and understand best practices for solving commonly faced problems using practical recipes.
What you will learn
Get to grips with data warehousing techniques aligned with Snowflake’s cloud architecture
Broaden your skills as a data warehouse designer to cover the Snowflake ecosystem
Transfer skills from on-premise data warehousing to the Snowflake cloud analytics platform
Optimize performance and costs associated with a Snowflake solution
Stage data on object stores and load it into Snowflake
Secure data and share it efficiently for access
Manage transactions and extend Snowflake using stored procedures
Extend cloud data applications using Spark Connector
