Data Panda lifts data out of your CRM, ERP, ecommerce, finance and product systems into the Fabric Data Warehouse on a known schedule. Once it sits in OneLake, Power BI Direct Lake, Copilot in Fabric and your existing Microsoft estate all read the same numbers without anyone exporting another extract.
Microsoft Fabric was announced at Build in May 2023 and reached general availability in November 2023 as a unified SaaS analytics platform on Azure. The Data Warehouse experience is one of seven workloads in Fabric, alongside Data Engineering (Spark notebooks and lakehouses), Data Factory (pipelines and dataflows), Real-Time Intelligence, Data Science, Databases and Power BI. All of them write to and read from the same store: OneLake, a single tenant-wide data lake built on Delta Parquet, with shortcuts that let one workspace point at data physically held in another without copying it.
The Fabric Data Warehouse itself is a fully managed, serverless T-SQL warehouse that runs queries directly against Delta tables in OneLake. It speaks the SQL Server T-SQL surface, supports cross-database queries between warehouses and lakehouses in the same workspace, and pairs natively with Power BI through Direct Lake mode, where reports query Delta files in OneLake without an import step or a DirectQuery round-trip. Billing runs on capacity units (CU) bought as a Fabric capacity (F2 through F2048 SKUs, or shared with the Power BI Premium P-SKUs), so warehouse compute, Spark, pipelines and Power BI rendering all draw from the same pool. For Microsoft-shop teams in BE and NL who already have Power BI Premium and Azure SQL on the floor, Fabric is the natural place to land the rest of the business so Direct Lake reports stop being demos and start being the actual finance and sales boards.
Reports read Delta tables in OneLake instead of importing or DirectQuery-ing for every refresh.
Operational data lands in the warehouse on a schedule that matches the business, not the loudest dashboard.
Copilot and the AI skills work against curated warehouse tables, not raw extracts.
Internal apps, Azure services and other workspaces read the same OneLake without copying data.
A list of concrete reports, automations and AI features we have built on Microsoft Fabric DWH data. Pick the one that matches your situation.
We already have Power BI Premium. Why move to Fabric?
Power BI Premium P-SKUs already give you a Fabric capacity, so the move is more of a flick than an investment in new licenses. The win is Direct Lake: reports stop relying on PBIX import refreshes and read Delta tables in OneLake straight away. The same capacity then carries the warehouse, the pipelines and the Spark workloads, instead of you running a separate Azure Synapse or Azure SQL bill next to Premium.
How is the Fabric warehouse different from a Fabric lakehouse?
Both write Delta tables to OneLake, but the warehouse is a fully managed T-SQL surface with cross-database queries, transactions and the SQL Server semantics finance teams are used to. The lakehouse is the Spark and notebook side, with the SQL endpoint as a read-only T-SQL view on top. In most BE/NL Fabric deployments we land raw and bronze in a lakehouse and curate the gold layer in the warehouse, because that is where Power BI Direct Lake and downstream T-SQL apps want to read.
Why does our Fabric capacity throttle when we add the warehouse?
Capacity units are shared across every workload in Fabric, so Power BI rendering, warehouse compute, Spark and pipelines all draw from the same F-SKU. A capacity sized for Power BI alone runs out of headroom the moment a warehouse load and a Spark notebook hit at the same time. Sizing per workload, scheduling heavy loads outside report hours and watching the Capacity Metrics app keeps the throttling out of the morning standup.
The CFO gets a Fabric-fed close pack that ties to the boekhouding. Revenue, margin and AR carry one definition, sourced from the same warehouse the sales board reads through Direct Lake, so month-end stops being three people reconciling Power BI exports.
Sales leaders see pipeline, forecast and quota next to invoiced revenue and product usage on warehouse-grade data. Direct Lake means the Power BI report stays current without an import refresh in between, and Copilot in Power BI answers questions against the same semantic model.
Operations and data leads track Fabric capacity unit usage, warehouse query cost and pipeline runtime in one Capacity Metrics view. The capacity bill becomes predictable, and the OneLake layout stops growing sideways with team-specific copies of the same Delta tables.
You keep the reporting tool you already have. We connect it to the warehouse where your Microsoft Fabric DWH 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.
Yes. Direct Lake mode reads Delta Parquet files in OneLake straight into the Power BI engine without an import refresh and without a DirectQuery hop to the warehouse engine. As long as the semantic model and the Delta tables stay compatible, queries fall back automatically to DirectQuery on the warehouse if a feature is not yet supported. The curated layer we build in the Fabric warehouse is exactly what Direct Lake wants to read.
Sized per workload, not per peak. Power BI rendering, warehouse loads, Spark notebooks and pipelines all draw from the same F-SKU, so an over-sized capacity for one workload subsidises the others quietly. Watching the Capacity Metrics app every cycle, scheduling heavy loads outside report hours and parking dev workloads on a smaller capacity keeps the bill flat without anyone reaching for autoscale at midnight.
It depends on which Synapse you mean. Synapse Dedicated SQL Pools (the warehouse) map cleanly onto a Fabric warehouse and Microsoft has positioned Fabric as the forward path. Synapse Spark and serverless SQL pools have analogues in Fabric Data Engineering and the lakehouse SQL endpoint. Most BE/NL Synapse customers we see migrate one workload at a time, starting with the warehouse on a curated layer in OneLake, and keep Synapse running until Power BI is on Direct Lake.
We review your Microsoft Fabric DWH setup and the systems around it. Together we pick the first thing worth building.