Leaders want one screen that tells them how the business is doing. The first decision is usually framed as a tool choice: buy a business intelligence (BI) platform such as Power BI, or build a custom dashboard. The more important decision sits underneath it, and we will come to that.
What a BI tool gives you
BI platforms such as Microsoft Power BI, Tableau, Looker and open-source options like Metabase are built for analysis and reporting. Power BI is a common choice in organisations already using Microsoft 365.
Strengths:
- Speed: connect to data sources, model the data and publish interactive reports in days or weeks.
- Self-service: analysts can explore data and build new reports without developers.
- Broad connectivity: ready-made connectors for databases, spreadsheets, cloud services and business applications.
- Governance features: row-level security, scheduled refresh, sharing and access management.
- Familiarity: users in Microsoft organisations already know the surrounding tools.
Limits:
- Design and interaction stay within the tool: you can style reports, but not fully control the experience.
- Licensing scales with use: costs depend on the plan and on how many people create and view reports, so check the current pricing for your expected audience.
- External audiences need more planning: showing reports to customers inside your own product usually needs an embedding setup and the right capacity licensing.
- Real-time and write-back are limited: BI tools are designed mainly for reading and analysing data, not for operational workflows.
What a custom dashboard gives you
A custom dashboard is built into your web application or product with your own code, usually with a charting library on top of an API that serves the data.
Strengths:
- Complete control of design, interactions and user experience, consistent with the rest of your product.
- Built for customers: usage-based views, branding, permissions and features that are part of what you sell.
- Real-time and operational: live updates, alerts and actions in the same screen (“approve”, “assign”, “reorder”).
- No per-viewer licences from a BI vendor.
Limits:
- Build and maintenance cost: every new chart or filter is development work.
- Less self-service: new questions usually mean new features rather than a drag-and-drop report.
Side by side
| Need | BI tool (e.g. Power BI) | Custom dashboard |
|---|---|---|
| Internal reporting and analysis | Strong fit | Usually overkill |
| Analysts building their own reports | Strong fit | Weak |
| Dashboards for your customers, in your product | Possible with embedding | Strong fit |
| Fully branded experience | Limited | Full control |
| Real-time updates and actions | Limited | Strong fit |
| Time to first version | Fast | Slower |
| Cost driver | Licences by plan and audience | Development and maintenance |
The decision that matters more: the data model
Whichever tool shows the numbers, trustworthy dashboards depend on what sits underneath:
- A single source of truth: data from operational systems brought together in a data platform or warehouse.
- Agreed definitions: what counts as revenue, an active customer or a resolved ticket, written down and implemented once.
- A shared semantic model: metrics calculated in one place and reused by every report, instead of each report doing its own maths.
- Quality checks and refresh monitoring, so people know when data is late or wrong.
The same foundations make data ready for AI later; see how to prepare your data for AI.
When two dashboards disagree, the problem is almost always here, not in the charting tool.
A common pattern that works
Many organisations use both:
- Build a shared data platform with agreed metric definitions.
- Use a BI tool such as Power BI for internal reporting and analysis.
- Build custom dashboards only where they are part of a product or an operational workflow, reading from the same data platform.
That way the numbers match everywhere, analysts stay productive, and custom development is spent where it creates value for customers.