Bringing trust, governance, and speed to the data stack

Hex integrates with dbt to pull metadata on freshness and tests right into the flexible notebook environment where you're writing queries.

How it works

When Hex has been connected to a dbt Cloud project, metadata on source freshness and tests will be surfaced directly in the schema browser. This lets users write queries with full confidence that the data they're returning is up to date and accurate, rather than just taking it on faith.

Bringing this metadata right into the data notebook where actual analytical work is happening gives data analysts and scientists the ability to move fast and be flexible, while knowing they aren't inadvertently accessing stale or inaccurate data.

snowflake Snowflake
in-use2 cells
vehicle_destinations16 cols, 192 rows
dbtModel2 min agogreen-tick Tests
VEHICLE_ID
string
MODEL
string
SPEED
number
BUILD_DATE
datetime
snowflake Snowflake
select
cast({{timeframe}} as timestamp) as month,
ship, destination,
sum(spice_tons) as spice_tons
from atreides.vehicle_destinations
group by 1,2,3
output-arrow
dataframe

"dbt and Hex make the data development environment so much easier to work with than any other combination of tools. Since itโ€™s all native, we donโ€™t need to wait for or build a custom adapter. I can instead focus on scaling my team, and building the best live shopping platform."

Emmanuel Fuentes, Head of Machine Learning & Data Platforms

Whatnot