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7.1 Visual Types and Selection

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Microsoft Power BI Data Analyst PL-300

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1 Introduction

About the PL-300 Exam The Power BI Ecosystem

2 Chapter 1: Get or Connect to Data

1.1 Data Source Types and Connections 1.2 Storage Modes: Import, DirectQuery, and Direct Lake 1.3 Data Source Settings and Parameters

3 Chapter 2: Profile and Clean the Data

2.1 Data Profiling in Power Query 2.2 Resolving Errors, Nulls, and Data Quality Issues 2.3 Data Types and Type Detection

4 Chapter 3: Transform and Load the Data

3.1 Column Transformations and Data Types 3.2 Grouping, Aggregating, Pivoting, and Unpivoting 3.3 Merge Queries, Append Queries, and Relationship Keys 3.4 Query Folding and Load Performance

5 Chapter 4: Design and Implement a Data Model

4.1 Star Schema Design 4.2 Relationships, Cardinality, and Cross-Filter Direction 4.3 Table and Column Properties 4.4 Calculated Columns and Calculated Tables

6 Chapter 5: Create Model Calculations with DAX

5.1 DAX Fundamentals and Measures 5.2 The CALCULATE Function 5.3 Time Intelligence Measures 5.4 Statistical Functions, Semi-Additive Measures, and Calculation Groups 5.5 Essential DAX Patterns and Functions Reference

7 Chapter 6: Optimize Model Performance

6.1 Performance Analyzer and DAX Query View 6.2 Model Size Reduction and Cardinality Management 6.3 DAX Optimization Patterns

8 Chapter 7: Create Reports

7.1 Visual Types and Selection 7.2 Visual Formatting and Conditional Formatting 7.3 Copilot in Power BI Reports 7.4 Report Page Configuration and Slicers

9 Chapter 8: Enhance Reports for Usability and Storytelling

8.1 Bookmarks, Navigation, and Drillthrough 8.2 Sorting, Selection Pane, Mobile Layout, and Accessibility 8.3 Export Settings and Automatic Page Refresh

10 Chapter 9: Identify Patterns and Trends

9.1 The Analyze Feature and AI Visuals 9.2 Using Copilot to Summarize the Semantic Model 9.3 Advanced Analytics Patterns

11 Chapter 10: Create and Manage Workspaces and Assets

10.1 Workspaces, Apps, and Content Distribution 10.2 Subscriptions, Alerts, and Semantic Model Refresh 10.3 Dashboards and Advanced Distribution

12 Chapter 11: Secure and Govern Power BI Items

11.1 Row-Level Security (RLS) 11.2 Sensitivity Labels, Item Access, and Governance 11.3 Deployment Pipelines and Content Lifecycle

7.1 Visual Types and Selection

Key Takeaways Explain This Topic AI

Power BI ships 30+ built-in visuals plus custom visuals from AppSource and organizational stores.

Choose a visual by the analytical question: comparison, trend over time, composition, distribution, relationship, or single value.

Tables and matrices show detailed data; matrices add row/column hierarchies, subtotals, and stepped layout.

Cards and KPIs highlight a single metric; gauges show progress toward a target; maps need geographic data categories.

Visual calculations (GA since May 2026) let report authors write running totals and other visual-scoped DAX without model measures, across Pro/PPU/Premium/Fabric tiers.

Last updated: June 2026

Quick Answer: Choose visuals by what you are analyzing: bar/column for comparison, line for trends, pie/donut for composition, scatter for relationships, cards for KPIs, and tables/matrices for detail. The PL-300 tests selecting the most appropriate visual for a given business scenario.

Choosing the Right Visual

  • Analytical Question Best Visual Types
  • Compare values Bar, Column, Clustered bar/column
  • Trend over time Line, Area, Line and clustered column
  • Composition Pie, Donut, Stacked bar/column, Treemap
  • Distribution Histogram, Box plot, Scatter
  • Relationship Scatter, Bubble
  • Geographic Map, Filled map, Shape map, Azure map
  • Single value Card, Multi-row card, KPI
  • Progress to goal Gauge, KPI
  • Detailed data Table, Matrix
  • Hierarchy Decomposition tree, Treemap, Matrix
  • Flow / stages Waterfall, Funnel

Core Visual Types

Bar and column charts compare values across categories. Use horizontal bars when category labels are long (product names) and vertical columns when categories are few with short labels. Stacked variants add composition; 100% stacked shows proportions.

Line and area charts show trends over continuous time. Line-and-clustered-column combos display two metrics (for example revenue bars with a margin line) on dual axes.

Pie and donut charts show parts of a whole. Limit to about 5-7 slices ; for many categories prefer a treemap or stacked bar.

Tables and matrices display detail. A matrix adds row and column hierarchies with expand/collapse, subtotals and grand totals, stepped layout, and conditional formatting, the pivot-table style.

Cards surface a single metric: Card for one big number, Multi-row card for several, and KPI for value plus trend and target.

Maps require geographic data: Map (bubbles), Filled map (colored regions), Shape map (custom boundaries), and Azure map / ArcGIS for advanced spatial analysis. Set the relevant Data Category (City, State, Country, Latitude/Longitude) so geocoding works.

  • Visual Use Case
  • Scatter Relationship between two numeric variables
  • Waterfall How an initial value grows/shrinks to a final value
  • Funnel Progressive reduction across stages (pipeline)
  • Treemap Hierarchical composition with nested rectangles
  • Decomposition tree AI-assisted root-cause drilldown
  • Ribbon Ranking changes over time
  • Gauge Progress toward a single target

Visual Calculations (DAX in Visuals)

Visual calculations let report authors write DAX directly on a visual, scoped to that visual's grid, without adding model measures. They reached general availability in the May 2026 Power BI update and are available across Power BI Pro, Premium Per User, Premium capacity, and Fabric F-SKU tiers. Running Total = RUNNINGSUM([Revenue])

  • Vs Previous = [Revenue] - PREVIOUS([Revenue])
  • 3-Month Avg = MOVINGAVERAGE([Revenue], 3)

Key visual-calculation functions include RUNNINGSUM , MOVINGAVERAGE , PREVIOUS / NEXT , FIRST / LAST , COLLAPSE / EXPAND , RANGE , and WINDOW . Because they operate on the visual's already-aggregated rows, they make running totals and percent-of-parent far simpler than the equivalent model DAX.

  • Scenario Use
  • Calculation needed in many visuals/reports Measure (reusable)
  • Calculation specific to one visual's layout Visual calculation
  • Running total over a visual's date axis Visual calculation
  • KPI shared across reports Measure
  • Paginated Reports

Paginated reports are pixel-perfect, print-ready reports for fixed layouts and full-row detail.

  • Feature Interactive Report Paginated Report
  • Best for Exploration Printing, formal documents
  • Layout Canvas, responsive Fixed, pixel-perfect
  • Data volume Aggregated Every row
  • Author tool Power BI Desktop Power BI Report Builder
  • Export PDF, PPTX, PNG PDF, Excel, Word, CSV, XML
  • Licensing Pro or higher Premium / PPU / Fabric required

Choose paginated for invoices, statements, fixed page dimensions, full-row output, or print/PDF distribution.

On the Exam

The PL-300 tests selecting the right visual for a scenario, tables vs. matrices, when paginated reports apply, visual calculations vs. model measures, and map data-category requirements.

Match the Visual to the Question, Not the Data

The exam's visual-selection items are really about analytical intent. Decide first what the user is trying to learn, compare, trend, compose, relate, distribute, or spotlight a single number, and the right visual follows. Comparisons across categories call for bar or column charts; trends over continuous time call for line charts; part-to-whole at a glance calls for pie, donut, or stacked bars (kept to a few segments); two-variable relationships call for scatter; and a single headline metric calls for a card or KPI. Reaching for a fancy custom visual when a clustered column answers the question is a classic wrong answer.

Tables vs. Matrices, and When Detail Beats Charts

A table is a flat list of rows and is the right choice when users genuinely need to read or export individual records. A matrix pivots data with row and column hierarchies, subtotals, grand totals, and stepped layout, the choice when users want cross-tabulated analysis like product-by-region. Both support conditional formatting (data bars, color scales, icons) that turns dense numbers into a scannable grid. When a report must show every transaction, fit a printed page, and include headers/footers, neither belongs on an interactive canvas, that is the paginated report scenario, authored in Power BI Report Builder.

Visual Calculations Change the Authoring Calculus

Now that visual calculations reached general availability in May 2026 across Pro, PPU, Premium, and Fabric tiers, report authors can express visual-scoped logic, running totals, moving averages, percent-of-parent, period-over-period deltas, directly on the visual with functions like RUNNINGSUM , MOVINGAVERAGE , and PREVIOUS , without cluttering the semantic model with single-use measures.

The exam-relevant judgment is scope: if the calculation only makes sense within one visual's grid and is not reused, a visual calculation is cleaner; if many visuals or reports need it, author a model measure so the logic stays centralized and governed.