This Company Is Reinventing Cloud Data Management With Python

Data engineering is a critical process for any business that relies on data to make decisions. As more companies come to depend on data, the need for efficient and effective data management solutions has never been greater.

dbt Labs recently announced that its data management platform, dbt, now supports data transformation in Python. In addition to SQL capabilities, this new capability will allow data teams to tackle statistical analysis and predictive modeling. Before this, working with Python and SQL required separate workflows and infrastructure.

"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 chief executive officer 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."

dbt Labs claims that the release of this new capability will allow the 16,000 organizations using dbt today to take advantage of Python capabilities available on major cloud data platforms. This includes Snowflake's Python Connector for Snowpark, BigQuery's Serverless Spark, and Databricks' Databricks SQL.

Whether dbt users prefer SQL or Python depends on the task. However, having the option to use either language will give data teams the flexibility they need to do the job.

"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 at 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."

Sudhir Hasbe, senior director of product management from Google Cloud, stated that dbt provided a flexible workflow for BigQuery customers to manage and help drive their data transformations. He believed that support for Python processing in BigQuery would give customers and the data community even more ways to solve business challenges with data.