dbt now supports Amazon Redshift data sharing: write across databases, isolate dev and CI, and run faster without copying data.

Learn how dbt State lets you reuse what hasn’t changed and cut data spend.

Analytics teams have always modeled data for BI. Context engineering models data for agents, starting with semantic search.

dbt v2, dbt State are GA and Fivetran + dbt Labs debuts Fivetran Context Layer, dbt Charts and a new open lakehouse vision

Every product announced at dbt Summit, from dbt v2 and dbt State to dbt Wizard and dbt Charts, and why each one matters.

dbt State is now generally available everywhere you run dbt. See how it cuts compute costs and speeds up development.

Meet the 2026 dbt Labs Partner of the Year winners: phData, Snowflake, Cívica, Datum Studio, and 66degrees.

Many AI projects are stuck. Don’t blame the models. The problem is a lack of trusted context. Here’s how you solve it.

As AI scales, cracks in data trust and governance start to show. Here's what breaks first, and what it takes to fix it.

Your compute platform and your transformation logic are two separate decisions. Most executives approve them as one.

dbt Core v1.12: what's new and how to upgrade.

We were burning through Gong's API to feed AI. Modeling the transcripts in the warehouse with dbt cut token costs 20x.

Why do some AI deployments yield great successes while so many still crash and burn? The answer is in the data.

How Fanatics cut warehouse compute by only rebuilding what's changed

The dbt Summit 2026 keynotes and the product sessions behind them.

First in a series on the shift from modeling data for dashboards to modeling context for agents. We start with our own Gong data.

The dbt Snowflake Native App retires in November 2026. Here's what it means for you.

AI has changed the game. dbt is changing along with it. Learn more about dbt Core v2.0 and the future of dbt itself.

Preview dbt Summit 2026 sessions by role: hands-on labs and breakouts for analytics engineers, data leaders, and execs.

Apache Ossie is currently undergoing incubation at The Apache Software Foundation (ASF).

Budgets aren't growing, but the work is. See how dbt customers recouped 58.7 FTEs in capacity, worth $1.75M a year.

Integral Ad Science used MCP to connect AI agents to dbt and Databricks, turning hours of dashboard debugging into minutes.

AI coding took off. AI pipeline management didn't. Here's a practical playbook for closing that gap.

Data platforms store information. Intelligence platforms govern meaning so AI can reason on it reliably.

See what Fivetran + dbt Labs shared at Databricks Data + AI Summit: dbt Wizard, dbt State, and dbt Core v2.0, plus what's next.

Two teams. Same metric. Different numbers. That's semantic debt, and AI will make it impossible to ignore.

dbt migrations underdeliver when teams rebuild legacy patterns in a new tool. Here's how to start fresh instead.

AI is reshaping the analytics engineer role. Here's what system design, governance, and AI context look like in 2026.

AI agents can run your pipelines. But who decides what "correct" looks like? The transformation layer does, and that layer is dbt.

Analytics engineers are already doing context engineering. Here's how your dbt project becomes context for AI.