Choosing & Formatting Visuals
Select the right visual for your data, format and configure visuals, apply themes and conditional formatting, and create visual calculations with DAX.
Picking the right chart
You wouldn’t use a hammer to tighten a screw. Each tool has a purpose — and each visual type in Power BI has a data story it tells best.
Bar charts compare categories. Line charts show trends over time. Maps show geography. Cards highlight single numbers. Choosing the wrong visual makes your data harder to understand, not easier.
This module covers which visual to pick, how to format it, and how to use themes and conditional formatting to make reports professional and readable.
Visual selection guide
| Data Story | Best Visuals | Example |
|---|---|---|
| Compare categories | Bar chart, Column chart | Revenue by product category |
| Show trends over time | Line chart, Area chart | Monthly sales over 2 years |
| Part of whole | Pie chart (few categories), Donut, Treemap | Market share by brand |
| Single KPI | Card, KPI visual | Total revenue: $1.2M |
| Detailed data | Table, Matrix | Sales by product, region, and month |
| Geographic data | Map, Filled map, Shape map | Sales by country/city |
| Relationship between two measures | Scatter plot | Revenue vs profit margin by product |
| Range/variance | Waterfall, Funnel | Revenue bridge: start → changes → end; Sales funnel stages |
| Multiple KPIs at a glance | Multi-row card, Gauge | Revenue, orders, margin on one card |
Riley at Coastal Fresh (🛒) builds a sales dashboard:
- Card: Total revenue ($1.2M) — instant headline number
- Column chart: Revenue by product category — compare categories
- Line chart: Monthly revenue trend — show change over time
- Map: Revenue by store location — geographic distribution
- Matrix: Revenue by region × quarter — detailed cross-tabulation
Formatting and configuration
Key formatting options (found in Format visual pane):
| Setting | What It Controls |
|---|---|
| Data labels | Show values on chart elements |
| Legend | Position and visibility of the colour key |
| Axis | Titles, ranges, formatting for X and Y axes |
| Colours | Change colours per category or data point |
| Tooltips | What appears when hovering over a data point |
| Title | Visual title text, font, alignment |
| Background | Visual background colour and transparency |
| Border | Visual border colour and width |
Themes
Themes apply a consistent look across all visuals on a report.
Built-in themes: View → Themes → choose from gallery Custom themes: Export a JSON theme file, modify colours, fonts, and defaults, then import it.
Nadia at Prism Agency (📊) creates branded themes for each client — matching their corporate colours. She exports a JSON theme, changes the colour palette, and imports it before building the client report.
Conditional formatting
Conditional formatting changes a visual’s appearance based on data values — colours, icons, data bars, and web URLs.
| Format Type | Example |
|---|---|
| Background colour | Cells turn red when profit margin is below 10% |
| Font colour | Negative numbers in red, positive in green |
| Data bars | Bar graph inside table cells showing relative size |
| Icons | Traffic light icons (green/yellow/red) based on KPI status |
| Web URL | Clickable links in a table |
How to apply: Select a visual → Format → pick the field → Conditional formatting → choose rule type
Kenji at Apex Manufacturing (🏭) uses conditional formatting on his production matrix: green background when output exceeds target, red when it falls short.
Exam tip: rules vs field value formatting
Conditional formatting has two modes:
Rules: You define thresholds (if value greater than 100, colour green). Good for fixed targets.
Field value: The colour comes from a column in your data (e.g., a hex colour code column). Good for data-driven formatting.
Gradient: Colour smoothly transitions between min and max values. Good for heat maps.
The exam tests all three — know when each is appropriate.
Visual calculations
Visual calculations are DAX expressions that run in the context of a visual rather than the data model. They can reference visual layout elements like axes and legends.
Running Total = RUNNINGSUM([Total Revenue])
% of Grand Total = DIVIDE([Total Revenue], COLLAPSEALL([Total Revenue], ROWS))
Rank = RANK()Visual calculations are created in the visual itself (select visual → New visual calculation) and can use functions not available in regular measures:
RUNNINGSUM— running total along an axisMOVINGAVERAGE— rolling averageRANK— position rankingCOLLAPSE— aggregate to a parent level (one level up)COLLAPSEALL— aggregate to the grand total level (highest level)EXPAND— drill into a child level
Visual calculations vs regular measures
| Feature | Visual Calculation | Regular Measure |
|---|---|---|
| Where defined | On a specific visual | In the data model |
| Reusable across visuals | No — tied to one visual | Yes — available everywhere |
| Can reference visual layout | Yes (axes, legends, hierarchies) | No |
| Functions available | RUNNINGSUM, RANK, COLLAPSE, COLLAPSEALL + all DAX | Standard DAX only |
| Best for | Running totals, ranks, % of visual total | General-purpose calculations |
Knowledge check
Riley needs to show how total revenue breaks down across 5 product categories. Which visual is most appropriate?
Kenji wants table cells to turn red when production is below target and green when above. What should he use?
🎬 Video coming soon
Next up: Slicers, Filters and Interactions — control how users explore your data.