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You're reading from  Snowflake Cookbook

Product typeBook
Published inFeb 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781800560611
Edition1st Edition
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Authors (2):
Hamid Mahmood Qureshi
Hamid Mahmood Qureshi
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Hamid Mahmood Qureshi

Hamid Qureshi is a senior cloud and data warehouse professional with almost two decades of total experience, having architected, designed, and led the implementation of several data warehouse and business intelligence solutions. He has extensive experience and certifications across various data analytics platforms, ranging from Teradata, Oracle, and Hadoop to modern, cloud-based tools such as Snowflake. Having worked extensively with traditional technologies, combined with his knowledge of modern platforms, he has accumulated substantial practical expertise in data warehousing and analytics in Snowflake, which he has subsequently captured in his publications.
Read more about Hamid Mahmood Qureshi

Hammad Sharif
Hammad Sharif
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Hammad Sharif

Hammad Sharif is an experienced data architect with more than a decade of experience in the information domain, covering governance, warehousing, data lakes, streaming data, and machine learning. He has worked with a leading data warehouse vendor for a decade as part of a professional services organization, advising customers in telco, retail, life sciences, and financial industries located in Asia, Europe, and Australia during presales and post-sales implementation cycles. Hammad holds an MSc. in computer science and has published conference papers in the domains of machine learning, sensor networks, software engineering, and remote sensing.
Read more about Hammad Sharif

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

Snowflake allows data to be shared not only with other Snowflake users, but also with non-Snowflake users. When sharing with a non-Snowflake user, a reader account must be created through which non-Snowflake users gain access to the shared data. Because reader accounts share the parent account's compute resources, some limits must be introduced on the reader account to avoid a hefty compute bill.

Through this recipe, you will explore how to limit the compute costs associated with data sharing when data is shared with non-Snowflake customers, and the compute of the data provider is used.

Getting ready

You will need to be connected to your Snowflake instance via the web UI or the SnowSQL client to execute this recipe. We will act as a data provider and create a reader account that can be subsequently used to share data with non-Snowflake users.

Since we will be creating a reader account, which is an account...

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Snowflake Cookbook
Published in: Feb 2021Publisher: PacktISBN-13: 9781800560611

Authors (2)

author image
Hamid Mahmood Qureshi

Hamid Qureshi is a senior cloud and data warehouse professional with almost two decades of total experience, having architected, designed, and led the implementation of several data warehouse and business intelligence solutions. He has extensive experience and certifications across various data analytics platforms, ranging from Teradata, Oracle, and Hadoop to modern, cloud-based tools such as Snowflake. Having worked extensively with traditional technologies, combined with his knowledge of modern platforms, he has accumulated substantial practical expertise in data warehousing and analytics in Snowflake, which he has subsequently captured in his publications.
Read more about Hamid Mahmood Qureshi

author image
Hammad Sharif

Hammad Sharif is an experienced data architect with more than a decade of experience in the information domain, covering governance, warehousing, data lakes, streaming data, and machine learning. He has worked with a leading data warehouse vendor for a decade as part of a professional services organization, advising customers in telco, retail, life sciences, and financial industries located in Asia, Europe, and Australia during presales and post-sales implementation cycles. Hammad holds an MSc. in computer science and has published conference papers in the domains of machine learning, sensor networks, software engineering, and remote sensing.
Read more about Hammad Sharif