Just like all data modeling, consistency and standardization is key when determining when and what to cast. BI tools require certain fields to be specific data typesĪ key thing to remember when you’re casting data is the user experience in your end BI tool: are business users expecting customer_id to be filtered on 1 or '1'? What is more intuitive for them? If one id field is an integer, all id fields should be integers.Differences in needs or miscommunication from backend developers.This typically happens for a few reasons: But what are the scenarios folks run into that call for these conversions? At their core, these conversions need to happen because raw source data doesn’t match the analytics or business use case. You know at one point you’re going to need to cast a column to a different data type. PostgreSQL 9.3 Schema Setup: CREATE TABLE tbl (col INT) INSERT INTO tbl VALUES (1), (10), (100) ALTER TABLE tbl ALTER COLUMN col TYPE CHARACTER VARYING (10) Query 1: SELECT col, pgtypeof (col) FROM tbl. You may also see the CAST function replaced with a double colon (::), followed by the data type to convert to cast(order_id as string) is the same thing as order_id::string in most data warehouses. You can convert from INTEGER to CHARACTER VARYING out-of-the-box, all you need is ALTER TABLE query chaning column type: SQL Fiddle. In addition, the syntax to cast is the same across all of them using the CAST function. Google BigQuery, Amazon Redshift, Snowflake, Postgres, and Databricks all support the ability to cast columns and data to different types. SQL CAST function syntax in Snowflake, Databricks, BigQuery, and Redshift A few reasons for that: data cleanup and standardization, such as aliasing, casting, and lower or upper casing, should ideally happen in staging models to create downstream uniformity and improve downstream performance. This function takes two arguments: the string to convert and the. Use the TONUMBER() function if you need to convert more complicated strings. The PostgreSQL database provides one more way to convert. However, the order_id and customer_id fields are now strings, meaning you could easily concat different string variables to them.Ĭasting columns to their appropriate types typically happens in our dbt project’s staging models. Notice that CAST(), like the :: operator, removes additional spaces at the beginning and end of the string before converting it to a number. Let’s be clear: the resulting data from this query looks exactly the same as the upstream orders model. After running this query, the orders table will look a little something like this: order_id
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