We said I do. Now, we’re joined at the DAG
Where did this data come from? What happened to it? Who's using it? Those three questions map to three parts of your stack — ingestion, transformation, and consumption. Data world's newest couple, Fivetran and dbt, are bringing all three into a single place for your humans and agents.
And here's what makes it different: Fivetran and dbt don't observe your pipeline from the outside. We run it. So it isn't scraped or pieced together after the fact; it falls out of the systems doing the work, which is what makes it timely, complete, trustworthy, and rich with context.
In this session, we’ll show you what a unified lineage graph looks like, from source connector to model to consumption. With this unified graph, new use cases become possible: real cost visibility tied to actual usage, PII that stays governed as it travels downstream, impact analysis past the dbt boundary, and agents that reason with the full picture. You’ll get a sneak peak into what’s possible, see real examples, and tell us what matters most.
Check out more sessions
- Lightning talks
$1B in transactions, 1 minute latency: dbt as production banking infrastructure
Scott Ziolko / KeepView session - Breakout session
An AlphaSense case study: scaling AI on enterprise data with dbt-first governance and context from...
Sarah Levy / EunoBrad Levy / AlphaSenseView session - Peer exchange
Empowering stakeholders in the age of AI
Lexi Galantino / ZiplineView session
