Secoda Product News – April 2025

When Andrew and I started Secoda, it was because we believed there had to be a better way to work with data. We were tired of the same problems that we faced daily like tracking down data owners, guessing which dashboard to trust, and getting blocked on questions we knew someone had already answered.

We believed there should be a better way to find, understand, and use data. Now with Secoda AI, that belief is a reality. Secoda AI is uniquely designed to help teams get faster and more accurate answers by connecting all the rich context across your data sources and assets.

What makes Secoda AI different is how it empowers spontaneous exploration and removes the friction between your curiosity and your data. It empowers users to explore data on a whim, without needing a dashboard or waiting for someone to build one. You get the answer in seconds without digging through raw data or navigating disparate tools.

This month, we’re introducing AI-generated visualizations to that experience. Now, when you ask a question in Secoda, the AI can automatically visualize data it understands across your stack. For instance, a team lead could ask, “What’s the monthly revenue breakdown by customer segment?” and Secoda will surface the chart instantly, pulling the correct tables, dimensions, and metrics. No SQL. No BI tools. Just an answer you can act on. By adding charting into the experience, we’re giving teams more ways to express and share their curiosity visually and collaboratively. 

This all works because of the breadth and depth of context Secoda has across your data ecosystem. While many AI tools are just working as LLM wrappers, Secoda taps into everything from metadata, models, pipelines, documentation, SQL queries, Slack conversations, and even usage patterns. It knows where your data is, what it means, how reliable it is, who uses it, and how it fits into your broader ecosystem. That rich context powers a far more accurate, helpful AI experience that feels more like a teammate than a chatbot.

And because Secoda connects across your modern data stack, from BI tools to transformation layers to your warehouse, it can pull in knowledge wherever it lives. We’ve designed it to integrate seamlessly, so you’re not starting from scratch or switching tools to get what you need. Here are some highlights from what we’ve shipped this month to make that experience even better.

Omni integration

We’re building on our goal to make context more portable with a new integration with Omni, a BI platform designed to help teams define business metrics once and reuse them everywhere. Instead of duplicating logic across dashboards, Omni lets teams govern metrics centrally so that everyone is working from a single source of truth.

Now, that structure flows directly into Secoda. We ingest models, dimensions, dashboards, and lineage, so teams can see exactly what the business is measuring and how it’s defined. With Omni and Secoda connected, teams can search across their entire data stack, from dbt to the BI layer, and see a unified view of lineage and ownership. It means fewer duplicated dashboards, fewer Slack threads asking for definitions, and more confidence in the numbers being reported.

Native Snowflake application

We’re excited to share that Secoda is now available as a Snowflake Native App on Snowflake Marketplace. This new deployment option gives teams the ability to monitor data quality, detect anomalies, and access metadata directly within the Snowflake environment, without any additional infrastructure setup. For teams with strict security or residency requirements, this offers a more flexible and secure way to adopt governance workflows. It’s a natural extension of our existing integration, which already includes lineage, query monitoring, and metadata ingestion. Stay tuned for more updates at Snowflake Summit as we continue to bring more of Secoda natively into Snowflake.

Improved connectors

In addition to the above, we’ve made targeted improvements to other integrations to help teams embed context more deeply into their workflows.

In GitHub, you’ll now see automated impact analysis surfaced directly in pull requests. When a dbt model is changed, Secoda identifies downstream effects and makes that information available before the change is merged. You can also sync metadata edits from Secoda, such as model or column descriptions, owners, and tags, back into your dbt project. These changes generate a pull request automatically, keeping documentation aligned and version-controlled.

All of these changes support our broader mission. We want anyone in the organization to be able to find what they need, when they need it, without starting from scratch.

There’s still a lot we’re excited to build. But more and more, we’re seeing teams solve the same problems that inspired us to start Secoda in the first place. What used to be a vision is now playing out in real workflows, across real organizations.

Thanks for being part of it.
Until next time,
Etai Mizrahi

P.S. If you're thinking about what's next for AI and data, join us at MDS Fest. It’s a free virtual event happening May 5–9 (next week!) with 70+ speakers from companies like AWS, Netflix, and Meta.

Save your spot → https://www.mdsfest.com/ 

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