How to load data into Snowflake schema

05 Oct 2023

Snowflake is a cloud-based data warehouse that allows you to efficiently manage and analyze large amounts of data. One of the key aspects of Snowflake is its ability to work with data organized in a snowflake schema.

In this article, we will walk through the process of loading data into a Snowflake schema. We’ll cover the steps involved and demonstrate how to accomplish this using SQL.

Snowflake Schema Overview

First, let’s briefly review what a snowflake schema is. In a snowflake schema, data is organized into multiple levels of tables connected through relationships. The center table, known as the fact table, contains the primary data, while the surrounding tables, known as dimension tables, provide additional context for the data.

Steps to Load Data into Snowflake Schema

Here are the steps you need to follow to load data into a Snowflake schema:

Create the necessary tables: Start by creating the fact and dimension tables in your Snowflake schema. You can use the CREATE TABLE statement in SQL to define the structure and datatypes for each table.
Load data into dimension tables: Once the dimension tables are created, you can load data into them. You can use the COPY INTO statement in Snowflake to load data from external sources such as CSV files or from other Snowflake tables.
```
 COPY INTO dimensions.customer
 FROM @my_stage/customer_data.csv
 FILE_FORMAT = (TYPE = CSV)
```
This example shows how to load data into the customer dimension table from a CSV file located in a Snowflake staging area called my_stage.
Load data into the fact table: After loading data into the dimension tables, you can load data into the fact table. The process is similar to loading data into dimension tables, but you might use a different file or table as the source.
```
 COPY INTO fact.sales
 FROM @my_stage/sales_data.csv
 FILE_FORMAT = (TYPE = CSV)
```
In this example, we load data into the sales fact table from a CSV file located in the my_stage staging area.
Establish relationships: Now that the data is loaded into the snowflake schema, you need to establish relationships between the fact and dimension tables. You can create foreign key constraints to enforce referential integrity and ensure the data is correctly linked.
```
 ALTER TABLE fact.sales
 ADD FOREIGN KEY (customer_id) REFERENCES dimensions.customer(customer_id)
```
This SQL statement adds a foreign key constraint to the sales fact table, referencing the customer_id column in the customer dimension table.

Conclusion

Loading data into a Snowflake schema is a straightforward process that involves creating tables, loading data into the dimension and fact tables, and establishing relationships between them. Snowflake provides efficient tools and SQL statements to handle these tasks, enabling you to effectively manage and analyze your data. Start leveraging the power of Snowflake’s snowflake schema today!

#snowflake #datawarehouse