Synopsis vs Power BI
A dashboard needs data underneath it.
Power BI is one of the best-value BI tools in the market — fast to chart, Excel-native, and everywhere Microsoft already is. But a dashboard is only as good as the modeled data beneath it, and Power BI doesn't ingest your source systems, build your warehouse, or model your data. Synopsis includes all of that, and the dashboards, in one platform that's live in days.
What Power BI is
Power BI is Microsoft's business-intelligence tool: a visualization and reporting layer that turns data into dashboards and reports, with tight ties to Excel, Azure, and the wider Microsoft ecosystem. It's excellent and affordable at what it does. What it doesn't do is stand up the data underneath it — Power BI doesn't connect to and ingest your business systems into a managed pipeline, build and maintain a warehouse, or automatically model, clean, and join your raw data into trustworthy entities. To feed it, teams add a warehouse (often Microsoft Fabric or Azure Synapse), an ingestion tool, a transformation framework, and the engineers to run them.
Power BI + the stack beneath it
A great dashboard tool, plus everything you assemble to feed it.
- Power BI — the dashboards: strong and affordable, but only as good as the data beneath it
- A warehouse — Fabric, Azure Synapse, or another store to hold modeled data
- An ingestion tool — to load your business systems into that warehouse
- Transformation & modeling — dbt or Power Query plus engineers to clean and join raw data
- Governance — a shared semantic model someone has to define and maintain
- A data team — to build the pipeline and keep the reports trustworthy
- Timeline — weeks to months of setup before the first dashboard reflects reality
Synopsis
One platform: the pipeline, the warehouse, and the dashboards, live in days.
- Dashboards & BI included — generated from a single prompt, no report-building project
- Ingestion built in — your systems connect and land clean, no pipeline to run
- The warehouse itself — open, queryable, and yours, on Apache Iceberg
- Modeling done for you — raw data becomes clean, joined entities automatically
- Metrics governed once — a semantic layer everyone shares, defined for you
- No data team required — we configure it with you
- AI-ready from day one — your AI tools query it over MCP, and it works in Excel too
Side by side
Power BI vs Synopsis, capability by capability.
| Capability | Power BI | Synopsis |
|---|---|---|
| Cloud warehouse & fast SQL | ○ | ● |
| Connects to your business systems | ◐ | ● |
| Data modeled, cleaned & joined for you | ◐ | ● |
| Ask across every system in plain English | ◐ | ● |
| Dashboards & BI included | ● | ● |
| Alerting on your own data | ◐ | ● |
| Metrics defined once, governed everywhere | ◐ | ● |
| Live in days without a data team | ○ | ● |
| One vendor for the whole pipeline | ○ | ● |
| Query-ready for your AI tools (MCP) | ○ | ● |
| Microsoft-ecosystem integration & price / Excel-native analytics | ● | ◐ |
● Included ◐ Possible with effort or extra tools ○ Not available
An honest take
Where Power BI is the stronger choice.
Price and Microsoft-ecosystem fit
If your company runs on Microsoft 365, Azure, and Teams, Power BI is hard to beat on both price and integration. It's bundled into plans many companies already pay for, and it plugs straight into the tools your team lives in every day.
Excel-native analysts
Power BI grew out of Excel, and analysts who think in PivotTables and formulas feel at home immediately. If your team's muscle memory is Excel, the learning curve is close to zero.
Deep, hand-crafted report design
For analysts who want fine-grained control over every visual, DAX measure, and report layout, Power BI offers mature, granular authoring built up over years. If highly customized, pixel-level reports are the goal, that depth is real.
The bottom line
Power BI is a strong, affordable dashboard tool — and if you already have a warehouse, a pipeline, and the team to model your data, it's a sensible way to visualize it. Synopsis is for the more common case: you want the dashboards and the answers without first assembling and running the stack that feeds them. You get ingestion, an open warehouse, automatic modeling, a governed semantic layer, and the BI on top — one platform, live in days, and it still works in Excel.
Questions
Is Synopsis a Power BI alternative?
For many teams, yes — but it's a broader shape. Power BI is the dashboard layer; you assemble a warehouse, ingestion, and modeling underneath it. Synopsis includes all of those plus the dashboards, so you're comparing 'Power BI plus a stack and a data team' against 'Synopsis on its own.'
Can Synopsis replace Power BI?
For most teams, Synopsis replaces the whole Power BI-based stack — the ingestion, warehouse, modeling, and the dashboards. If you have analysts who need pixel-level report authoring in Power BI's designer, or you're deeply committed to the Microsoft and Fabric ecosystem, some teams keep Power BI on top while Synopsis handles the pipeline and modeling underneath.
Does Synopsis work with Excel and Microsoft tools?
Yes. Your modeled data stays open and queryable, and it's available in Excel and Google Sheets, in Slack, and to your AI tools over MCP — so analysts who live in spreadsheets keep working the way they always have.
Do I need a data team to use Synopsis?
No — that's the core difference. A Power BI dashboard is only as trustworthy as the modeled data beneath it, which normally takes engineers to build. Synopsis connects your systems, models the data automatically, and delivers dashboards in days, with no data team required on your side.
See it on your own data.
Bring a question you've been trying to answer with Power BI and the tools around it.
