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Consultant KB for Microsoft Power BI: semantic models, DAX and modelling, Power Query and dataflows, reports and visuals, the service and workspaces, capacity and performance, embedding and integration, governance and security, ALM and deployment, and licensing, plus cross-cutting decision guides. Scoped to Power BI, with Microsoft Fabric covered where it touches Power BI directly. Implementation notes, configuration decisions and the gotchas that bite on real projects. Populated by the daily author agent from the Power BI release plans, docs repo and product blog, plus the author's own consultant notes.

power-bi/04-reports-and-visuals/feature-core-visuals.md
feature-core-visuals.mdv1 · history
CurrentApplies to BothUpdated last monthSource Microsoft Learn ↗

What it does

The core visuals are the chart types shipped in the Visualizations pane of Power BI Desktop and the service — bar and column, line, area, combo, scatter, pie and donut, treemap, map and filled map, gauge, card, KPI, table, matrix, slicer, and the rest. They're available everywhere with no import, no governance question and no third-party dependency.

Key facts

  • The set is identical in Desktop and the service, so anything you build in one renders in the other.
  • Visuals can be unpinned from the pane by right-clicking, and the whole pane reset with Restore default visuals from the ellipsis.
  • Small multiples split a single chart into a grid of the same chart by a category. The grid is adjustable up to six by six.
  • Small multiples don't support the hierarchical axis — the axis falls back to a concatenated format.
  • Different visual types apply different data point limits and reduction strategies, so a visual can be silently sampling rather than showing you everything.
  • Cross-filtering and cross-highlighting are on by default between visuals on a page. Line charts, scatter charts and maps can be cross-filtered but not cross-highlighted.
  • Matrix visuals built from fields across multiple tables can throw errors on other visuals when you cross-highlight multiple items at different hierarchy levels.

When to use / skip

Start every visual with the question the number is answering. Comparison across categories is a bar chart — horizontal if the labels are long, which they usually are. Change over time is a line chart. Composition is a stacked bar, or a table, and almost never a pie. Precise values people will read off and copy into an email belong in a table or matrix, not a chart. Small multiples are the right answer when someone asks for "the same chart for each region" and you were about to build eight charts by hand. Only reach outside the core set once you've established the core set genuinely can't do it — the answer is usually that it can, just not in the exact style someone saw on LinkedIn.

Configuration decisions

  • Sort order on every categorical visual, set deliberately rather than left to default — it also drives what the accessible Show Data table shows.
  • Whether data labels are on, and if so at what precision. Every label is competing with the data.
  • Aggregation per field, checked explicitly. Power BI's default is Sum and it will happily sum an ID column.
  • Which axis is fixed and which is auto-scaled, particularly on anything people compare side by side.
  • Whether a visual is a chart at all, or whether the audience actually wants a table.
  • Whether small multiples or a slicer-plus-single-chart better fits how people use the page.

Gotchas

  • Pie and donut charts with more than a handful of slices are unreadable, and people will still ask for them. Offer a sorted bar chart first.
  • Dual-axis combo charts invite false correlation. Two independently scaled axes can be arranged to show almost any relationship.
  • Truncated or auto-scaled y-axes exaggerate small differences. Fine for exploration, dangerous on a board pack.
  • Data point limits mean a scatter chart of a million rows isn't showing a million points. The visual won't tell you it reduced.
  • Maps look impressive and usually communicate less than a sorted bar chart of the same data. Use them when geography is the point, not as decoration.
  • Gauges need a meaningful target. Without one they're a card with extra ink.

Consultant notes

  • The default core set covers well over 90% of real client requirements. Say so early — it heads off a custom visual conversation you'd rather not have later.
  • When a client sends over a chart they like from elsewhere, work out what question it answers before agreeing to reproduce it. Often the answer is a simpler chart.
  • Small multiples are an easy win to demo. Clients consistently underestimate them and they replace a lot of copy-paste work.
  • Watch for the maker who's discovered conditional formatting. Colour carries meaning, and once everything is coloured nothing is.

Worth another look after a few monthly Desktop releases — the core visual set and its formatting options move steadily.

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