Snowflake ETL Best Practices You Should Know About

Snowflake is a cloud data warehouse that comes along with a fast, reliable, and robust engine for strong and querying data. It is built on amazon web service, Microsoft azure, and google infrastructure. in addition, it is a fully managed cloud data warehouse that helps companies and organizations store data and analytics.

 

Apart from fast query performance, it also offers data security using policy controls. Also, it is highly scalable and can easily handle terabytes of data. Most users can easily load data from multiple sources to the warehouse snowflake ETL process. Here are some of the best practices that you can follow while performing the snowflake ETL process.

 

Data Storage Considerations

Snowflake provides an array of multiple characteristicsfor data that is stored. Continuous data protection which includes fail-safe and time travel is given to all accounts for no additional cost. This doesn’t mean that CDP will not have an impact on your storage costs. Without that, it will.

 

Point to note, your account will be charged for all the data stored in schemas, tables and databases created in your snowflake architecture. Based on the type of data stored, CDP has an impact on the storage costs. Once the data leaves the fail-safe, storage costs will be incurred.

 

Data Staging Considerations

Both snowflake and your data source allow stage references via paths. While performing snowflake ETL, it is a good practice to stage regular data sets by partitioning them into logical paths. This could include details such as source identifiers or geographical locations, along with the date when the data was written.

 

Such exercise will provide you with flexibility to copy files by path using a single command. It will allow you to take advantage of snowflakes parallel operations by letting you execute multiple statements that match a list of files.

 

Bottom Line

We believe that this article will help you learn how snowflake ETL practices helps users to load data from data sources of a warehouse. Also, you read some of the best practices to follow while performing the snowflake ETL process.