Looking at example dashboards is the fastest way to figure out what your own report should do. The best ones aren't about flashy visuals — they answer a specific question for a specific person in a few seconds. Below are ten dashboard types that cover most of what businesses actually build, with the audience, the visuals worth copying, and the metrics that matter for each.
A quick note on terminology: in the Power BI Service a "dashboard" is technically a single page of pinned tiles, while a multi-page file is a "report." Most people use "dashboard" loosely to mean either. Everything here applies to both, and every example sits on top of a semantic model (the data layer with tables, relationships, and DAX measures — what Microsoft formerly called a "dataset").
What separates a good dashboard from a busy one
Before the examples, a few principles show up in every strong report:
- One audience, one question per page. An executive page and an analyst page should not be the same page.
- KPIs first, detail later. Put four to seven headline numbers across the top, supporting charts below, and granular tables on drill-through pages.
- A clean model underneath. Nearly every example here works best on a star schema: one fact table (transactions, events) surrounded by dimension tables (date, product, customer, region). This keeps DAX simple and visuals fast.
- Restraint. Roughly six to eight visuals per page, a consistent palette, and a real date table marked as a date table so time intelligence works.
If your colors and fonts are all over the place, a consistent palette does more for perceived quality than any single chart. You can generate a reusable JSON theme with the free Power BI theme generator.
1. Executive KPI dashboard
Who uses it: CEOs, founders, and leadership teams who want the health of the whole business on one screen.
Key visuals: A top row of KPI cards (or the multi-row card visual), a couple of trend lines for revenue and margin, a small map or bar chart for regional performance, and a single "needs attention" table. Keep it skimmable.
Key metrics: Revenue, gross margin %, profit, cash position, headcount, and one or two North Star metrics specific to the business (such as active customers). Each KPI should show the value plus a comparison to target or prior period.
Revenue YoY % =
VAR CurrentRevenue = [Total Revenue]
VAR PriorRevenue =
CALCULATE ( [Total Revenue], SAMEPERIODLASTYEAR ( 'Date'[Date] ) )
RETURN
DIVIDE ( CurrentRevenue - PriorRevenue, PriorRevenue )
2. Sales performance dashboard
Who uses it: Sales managers, reps, and revenue leaders tracking pipeline and quota.
Key visuals: A funnel for pipeline stages, a bar chart of sales by rep or region, a line chart of bookings over time, and a matrix of deals by stage with conditional formatting. Slicers for time period and territory are essential.
Key metrics: Total bookings, win rate, average deal size, sales cycle length, quota attainment, and pipeline coverage (pipeline ÷ target). Putting the rep field on an axis with a single measure beats writing a separate measure per rep, and a "% of total" calculation reads more clearly than raw values.
3. Finance / P&L dashboard
Who uses it: Controllers, FP&A teams, and CFOs.
Key visuals: A profit-and-loss matrix (accounts down the rows, months across the columns), a waterfall chart showing how you got from revenue to net income, and variance bars for budget vs. actual.
Key metrics: Revenue, COGS, gross and operating margin, EBITDA, budget variance, and trailing-twelve-month figures. The waterfall is the signature visual here — it turns a static P&L into a story.
| Visual | What it answers |
|---|---|
| P&L matrix | Where did the money go, line by line? |
| Waterfall | How did we get from gross to net? |
| Budget vs. actual bars | Where are we off plan, and by how much? |
4. Marketing analytics dashboard
Who uses it: Marketing managers and demand-gen teams.
Key visuals: Channel comparison bars (paid, organic, email, social), a conversion funnel from impression to lead to customer, and a trend line for spend vs. leads. A donut for channel mix works if you keep the categories few.
Key metrics: Cost per lead, cost per acquisition (CAC), conversion rate by stage, return on ad spend (ROAS), and marketing-sourced pipeline. Avoid the trap of one card per channel — use a single measure with the channel field on the axis instead.
5. Operations dashboard
Who uses it: Operations managers, plant or logistics leads, and service teams.
Key visuals: Gauges or KPI cards for SLA and uptime, a line chart of throughput or volume by day, and a matrix shaded with conditional formatting to surface bottlenecks by location or shift.
Key metrics: On-time delivery %, cycle time, capacity utilization, defect or error rate, and SLA adherence. Operations dashboards often refresh frequently, so a lean model and incremental refresh pay off.
6. HR / people dashboard
Who uses it: HR leaders, people-ops teams, and department heads.
Key visuals: A headcount trend, a donut or bar for department breakdowns, a turnover line chart, and a table of open requisitions. A decomposition tree is great for slicing attrition by cause.
Key metrics: Headcount, turnover/attrition rate, time-to-hire, offer acceptance rate, and tenure distribution. Handle this data carefully — apply row-level security if managers should only see their own teams.
7. Project / portfolio dashboard
Who uses it: Project managers and PMOs tracking delivery.
Key visuals: A Gantt-style timeline (available as a custom visual from AppSource), status cards (on track / at risk / late), a milestone table, and a stacked bar of tasks by status.
Key metrics: % complete, budget burn, schedule variance, open vs. closed tasks, and risk count. Conditional formatting that turns at-risk items red is the difference between a report people read and one they ignore.
8. Customer / retention dashboard
Who uses it: Customer success, account managers, and subscription/SaaS teams.
Key visuals: A cohort retention matrix, a churn trend line, a bar chart of revenue by segment, and a scatter plot of usage vs. value to spot accounts at risk.
Key metrics: Net revenue retention (NRR), gross churn, customer lifetime value (LTV), monthly recurring revenue (MRR), and active users. Cohort analysis leans on a solid date dimension and well-structured DAX.
9. Inventory / supply dashboard
Who uses it: Inventory managers and retail or warehouse operations.
Key visuals: Stock-level bars by SKU or category, a reorder-point table with conditional formatting, a turnover trend line, and a card row for total stock value.
Key metrics: Units on hand, inventory turnover, days of supply, stockout count, and carrying cost. A simple measure that flags items below the reorder point makes the table self-explanatory:
Below Reorder Point =
SUMX (
VALUES ( Product[SKU] ),
IF ( [Units On Hand] < [Reorder Point], 1, 0 )
)
10. Web / digital analytics dashboard
Who uses it: Growth, content, and ecommerce teams.
Key visuals: Sessions and users trend lines, a bar chart of top pages or sources, a funnel from visit to conversion, and a map for geography.
Key metrics: Sessions, users, bounce rate, conversion rate, average session duration, and revenue per visit. If you're pulling from an export rather than a live connector, Power Query is where you shape the messy raw data before it hits the model.
How to turn an example into your own report
Pick the example closest to your need, then work backwards:
- List your four to seven headline metrics first. The KPIs decide everything else.
- Sketch the model. Identify your fact table and the dimensions you'll slice by, then build a proper date table.
- Write measures, not calculated columns, for anything that aggregates. Measures respond to filters and keep the file small.
- Lay out top-down: KPIs at the top, trends in the middle, detail at the bottom or on drill-through.
- Apply one theme so every page looks like it belongs to the same report.
For more on the foundation, see our guides on building a star schema and writing your first DAX measures.
Get a finished version of any of these
If you'd rather skip the modeling and formatting, that's what Instant PowerBI is for. Send us your raw CSV or Excel file, tell us which of these dashboard types you want, and you'll get back a finished, branded Power BI report — a clean star-schema model, DAX measures, and a polished layout — that opens in the free Power BI Desktop. Start here and turn your data into a dashboard you'd be proud to present.
Frequently asked questions
What is a Power BI dashboard?
In the Power BI Service, a dashboard is a single-page canvas of pinned tiles from one or more reports, used for at-a-glance monitoring. In everyday speech people also call a multi-page Power BI report a 'dashboard.' Both are built on a semantic model (the data layer with tables, relationships, and DAX measures) and viewed in the free Power BI Desktop or the Power BI Service.
What makes a good Power BI dashboard?
A clear purpose and audience, a handful of KPIs at the top, supporting charts that explain the 'why,' and consistent formatting. Good dashboards are built on a clean star-schema model with well-named DAX measures, load fast, and limit themselves to roughly six to eight visuals per page so the main message is obvious within a few seconds.
How many KPIs should a dashboard show?
Aim for about four to seven headline KPIs on the top row of an executive or summary page. Many more than that and the page becomes a wall of numbers with no hierarchy. Put secondary metrics on drill-through pages or further down the page so the most important figures get visual priority.
Is Power BI free to use?
Power BI Desktop, the authoring app, is free to download and use on Windows. To publish and share reports with others in the Power BI Service you generally need a Power BI Pro license (roughly $14 per user per month as of 2026), or capacity-based licensing such as Premium Per User or Microsoft Fabric for larger deployments. Pricing changes over time, so check Microsoft's site for current figures.
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