Data Panda lands the data from your CRM, ERP, ecommerce and finance systems in one warehouse, then feeds Power BI from a single semantic layer. Reports stop disagreeing with each other and your DAX models stop multiplying.
Power BI became generally available in July 2015 and grew into the dominant BI product in the Microsoft-stack mid-market. It runs as a Windows desktop tool for authoring, a cloud service for sharing, mobile apps for consumption, and an on-premises Report Server for tenants that cannot move to the cloud. Pricing splits roughly into Free for personal use, Pro at $14/user/month for sharing, Premium Per User at $24/user/month for larger models, and Premium Capacity (now folded into Microsoft Fabric) for tenant-wide deployments.
Since the Microsoft Fabric launch in May 2023, Power BI sits inside Fabric as the BI workload on top of OneLake. That changes how the model layer behaves and where Premium capacity is billed, but the day-to-day analyst experience is still Power BI Desktop, Service and DAX. The hard problem in most BE/NL deployments isn't the tool, it is what feeds it. Reports built straight on Exact Online, an Odoo replica and a Salesforce export end up with three versions of revenue, three definitions of customer and three refresh schedules. We feed Power BI from one warehouse so the semantic model is built once and the dashboards stop arguing.
Power BI reports built on a warehouse semantic layer instead of five direct connections.
Dataset refresh runs against the warehouse, not against live operational systems.
Power BI Copilot and AI visuals work better when the model is consistent.
Power BI embedded in Teams, SharePoint or a custom portal stays in sync with the rest of the business.
A list of concrete reports, automations and AI features we have built on Power BI data. Pick the one that matches your situation.
Why does our Power BI revenue not match the finance report?
Almost always because the dashboard pulls Salesforce or HubSpot directly while finance reads Exact Online or Business Central. With one warehouse feeding Power BI, revenue has one definition and one source. The semantic model carries it once and every report reuses it.
Our dataset refresh keeps timing out. How do we make this stop?
Refresh failures usually trace to too many direct connections, oversized Import models or queries that compete with live ERP traffic. A warehouse-fed Power BI model refreshes one source on a known cadence, with row counts and runtime monitored. Pro models stay under the 1 GB cap, PPU and Fabric capacity scale beyond that.
We have eleven .pbix files with overlapping logic. How do we consolidate?
Start by mapping which datasets duplicate the same measures, then promote one shared semantic model in the Power BI Service. The duplicate files become thin reports that connect live to that model. The warehouse provides the consistent fact and dimension tables underneath, so the cleanup holds.
The CFO finally gets a Power BI close pack that ties to the boekhouding. Revenue, margin and AR all carry one definition, sourced from the warehouse, so Monday morning is reading the report instead of debugging it.
Sales leaders see pipeline, forecast and quota next to invoiced revenue and product usage on one Power BI workspace. The same numbers travel to Teams, the Monday standup and the QBR pack without copy-paste.
Operations leads track throughput, cycle time and SLA from the same warehouse Finance reads. Power BI alerts fire on real anomalies, not on a refresh that picked up a half-loaded export.
These are the 9 tables we currently pull from Power BI 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 Power BI 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.
Either path works. We can deliver a warehouse with curated facts and dimensions and let your analysts build the .pbix on top, or we can ship a shared semantic model in the Service that your reports connect to live. Most BE/NL clients pick the second path because it stops measure duplication across .pbix files.
Fabric is fine to land on. We can publish the warehouse to OneLake as a Fabric Lakehouse or Warehouse, so Power BI reads it natively without a gateway. If you are not on Fabric capacity yet, we feed Power BI through a regular DirectQuery or Import connection from the warehouse, which works the same on Pro and Premium Per User.
No. Pro at $14 per user per month is enough for many BE/NL mid-market deployments, with Premium Per User at $24 if you need larger models or paginated reports. Premium Capacity (now folded into Fabric) only kicks in when you want capacity-based licensing or workloads beyond Power BI itself.
We review your Power BI setup and the systems around it. Together we pick the first thing worth building.