Data Panda lands the data from your CRM, ERP, ecommerce and finance tools in a warehouse and feeds Metabase from there. Questions stop hammering your live OLTP, definitions stop drifting per dashboard, and the team keeps the open-source feel without the open-source mess.
Metabase started in 2014 in San Francisco, founded by Sameer Al-Sakran. It ships in three shapes: the open-source edition under AGPL v3 that any team can self-host, Metabase Cloud as the managed SaaS, and Metabase Pro and Enterprise tiers on top of either self-hosted or Cloud for advanced features like SSO, audit logs, sandboxing and embedding. The product line claims more than 50,000 organisations using it, which makes it one of the largest open-source BI footprints around.
The appeal is the low barrier to entry. A non-analyst can build a question with the point-and-click query builder, an analyst can drop into the SQL editor for the same data, and dashboards share by URL or email subscription. The catch in BE/NL mid-market deployments is the same one Tableau and Power BI face: the moment Metabase is pointed at three operational databases instead of one curated layer, every dashboard becomes a small disagreement. Question sprawl, cached-vs-live drift and the ten-people-saved-the-same-question problem all start there. We feed Metabase from one warehouse so the BI tool stays the friendly part and the data stays the trustworthy part.
Metabase questions and dashboards read from a warehouse model with one definition per metric.
Metabase reads the warehouse on a known cadence instead of querying the live OLTP.
Metabase's AI features and natural-language questions answer from curated tables.
Metabase Embedding shows customer-facing dashboards on the same warehouse data your team uses.
A list of concrete reports, automations and AI features we have built on Metabase data. Pick the one that matches your situation.
How many of our saved Metabase questions calculate revenue differently?
Run the saved-question collections through one shared warehouse model and the duplicates surface fast. Most BE/NL Metabase instances older than two years carry three or four versions of revenue: one from the CRM, one from the billing tool, one from the boekhouding. Reconciling those to a single warehouse definition turns the next steering committee into a discussion about the business, not about whose dashboard is right.
Why is our production database slow at month-end?
Often because Metabase is still pointed at it. Long-running SQL questions run against the same OLTP that handles checkout, ERP writes and CRM updates. Moving Metabase onto a warehouse fed by Data Panda takes the analyst load off production and gives the dashboards full history at the same time.
Should we move from self-hosted Metabase to Metabase Cloud?
Cloud takes the upgrade and patch lag off your plate, which is the most common reason self-hosted instances fall a year behind. Either path works on a warehouse-fed setup, because the data layer is decoupled from where Metabase itself runs. The decision becomes about where you want to spend operations time, not about data.
Finance gets a Metabase collection where revenue, AR and margin tie back to the boekhouding instead of inventing themselves per question. Month-end stops being three people comparing dashboards, and the CFO can subscribe to a weekly recap that already reconciles.
Sales sees pipeline, usage and renewal risk in one Metabase view, with the same customer master Finance and CS read. Forecast meetings stop being a debate about whose saved question is the right one, and quota reporting carries one definition end to end.
Operations and product leads get warehouse-backed dashboards on the open-source BI the team already likes. The production database stops being the place analysts run heavy SQL on, and saved questions stop multiplying because the curated layer covers the common asks.
These are the 7 tables we currently pull from Metabase into your warehouse. Query them directly in SQL, join them to the rest of your stack, or build reports on top.
Missing a table you need? We can extend the sync. Tell us what is missing and we will build it for you.
You keep the reporting tool you already have. We connect it to the warehouse where your Metabase data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Both paths work. The warehouse is the source of truth, and Metabase reads it through a regular database connection. Open-source self-hosted handles a lot for free, Metabase Cloud removes the upgrade and patch effort, and Pro or Enterprise add SSO, sandboxing, audit logs and embedding when you need them. The data layer stays the same regardless of which tier the BI tool runs on.
Start with the Metabase audit logs to find which questions and dashboards still get opened, then map the survivors against the warehouse model. The duplicates collapse into shared questions on curated tables, the stale ones move to an archive collection, and new asks land on the curated layer instead of in someone's personal collection.
Yes, and it is one of the better fits. Metabase supports static and interactive embeds, with row-level sandboxing on Pro and Enterprise, so a single warehouse can drive both the internal team's Metabase and the customer-facing dashboards in your product. One curated model, two audiences, no copy-paste reporting database in between.
We review your Metabase setup and the systems around it. Together we pick the first thing worth building.