Building a data warehouse in the cloud using Snowflake

The continued presence of on-premises data warehouses represents an increasing burden given it requires complex integrations comprising of both code and infrastructure [1]. When most of a company’s assets are in the cloud, establishing and maintaining data warehousing processes is vital for a business's success.

Building a data warehouse in the cloud using Snowflake can help companies of all sizes move to a modern cloud data warehouse.

Model of Snowflake warehouse

Snowflake as the data warehouse home

What is Snowflake?

Snowflake is a parallel processing data environment that lives in the cloud. In context of this article, Snowflake is the housed location for the data warehouse and all data warehouse related activities.

Benefits of Snowflake

Speed

• Snowflake has customizable warehouses (compute nodes) that can be adjusted to fit the volume of data as needed, allowing for speedy updates to the data warehouse
• Querying Snowflake from a reporting tool is quite fast, enabling users to quickly gain data insights from the model
• Querying can be improved by establishing partitioning practices to allow Snowflake to prune queries for better performance [2]

Administration

• Administration of Snowflake is easily manageable and accessible, allowing more time to distribute the data to the business

Connectivity

• Snowflake can connect to different cloud service providers to capture data from the business
• Snowflake also offers a variety of connections to different tools to allow for visualization and analysis, including but not limited to Power BI, Analysis Services, Python and C#