dbt

…test all the different AIs, all the different LLMs, be able to connect to all the different databases, work with teams, not just in the ecosystem of Google, but, you know, Snowflake, Databricks, the DBT community is amazing, and you you can just move so much faster and learn so much quicker.…

…And the difference is that if you use an agent to accomplish the similar task, let's say building a new model in DBT Wireflow, is that an agent would actually be able to not only write the code for you, but execute that code against the database, get the results, evaluate the results, put the code into, let's say, DBT model, run DBT,…

…And then oftentimes you have something like dbt, which is how you take it.…

…So there's a, a DBT pipeline on top of Snowflake 5 transfer ingestion.…

…So say yes from Microsoft Looker, uh, more recently and uh, then the headless ones like DBT Cube at scale even more recently than that.…

…peaker A: Yeah, from the cloud data platform perspective, uh, we have Snowflake as our uh enterprise data platform and um, we use dbt uh primarily for uh, our data transformation and um, Airflow uh, is sitting in the middle of that ecosystem primarily for data pipelines and orchestration.…

…Like historically there's always like look at any Fortune 500 companies like roughly the same stack for analytical databases, right? Like okay, fivetran to get data in, dbt, to run transformations, looker, tableau, Omni, um, hex, kind of whatever to run analytics.…

…Pipeline development could be dbt, could be Talend, or Informatica or Python.…

…Then there is DBT for data transformations.…