dbt Labs, the pioneer in analytics engineering, announced during the keynote of dbt Labs’ Coalesce 2022, that it has added support for data transformation in Python to dbt. This will supplement existing SQL capabilities and allow data teams to tackle new categories of problems, including statistical analysis and predictive modeling. dbt users will now be able to deploy Python and SQL from within the same workflow without the need for additional infrastructure.
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dbt has emerged as an industry standard for data transformation in the cloud. With this release, the 16,000 organizations using dbt today can leverage the Python capabilities available on major cloud data platforms. Snowflake’s Snowpark for Python and BigQuery’s Serverless Spark, as well as Databricks’ expansion into data analytics workflows with Databricks SQL, have elevated the role of Python in the modern data stack. dbt users will have the option of choosing the best language — SQL or Python — for the task at hand.
“Snowflake’s partnership with dbt Labs has been instrumental for modern analytics as we work towards enabling data teams to securely and collaboratively deploy SQL code to production,” said Torsten Grabs, Director of Product Management, Snowflake. “With dbt Labs’ introduction of Python models and Snowflake’s Snowpark for Python, joint customers can now effortlessly combine the power of SQL and Python for modern analytics, and benefit from the wealth of data processing innovation in the Python community. This will make it even easier for analytics, data engineering, and data science teams to be productive and collaborative in the Data Cloud.”
“We created dbt to harness the power of the modern cloud data platform and empower all data practitioners to participate in the data transformation process. Six years ago, that meant working exclusively in SQL, the native language of the warehouse,” said Tristan Handy, Founder and CEO of dbt Labs. “Today, with advancements across data platforms, we’re excited to bring the power and accessibility of dbt to a new set of data workloads.”