Guide to dbt Data Quality Checks

dbt (data build tool) is an open-source command-line tool that enables data teams to orchestrate data transformations and check data quality. It features built-in data quality checks, which help maintain data accuracy and consistency across the entire data processing pipeline. Implementing dbt data quality checks involves identifying the data to be tested, defining testing criteria using SQL queries, setting up a dbt project, and running tests manually or on a schedule. Other useful tools for maintaining data quality include Great Expectations, Airflow, and Snowflake.