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Power BI Report Visualization Designer

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Design effective and engaging Power BI reports with expert guidance.

by github37.7k stars on github/awesome-copilot
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Updated Aug 10, 2026
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What Power BI Report Visualization Designer does

The Power BI Report Visualization Designer skill provides a comprehensive framework for creating user-friendly and accessible reports tailored to specific business needs. By leveraging a structured design consultation process, this skill helps users gather initial requirements, analyze data context, and define technical specifications essential for effective report design. This ensures that the reports not only communicate insights clearly but also support data-driven decision-making effectively.

The skill emphasizes a methodical approach to chart selection, guiding users through various visualization types based on the nature of their data and the insights they wish to convey. From comparison and trend analysis to composition and distribution, users can choose the most appropriate visualizations that enhance understanding and engagement. Additionally, it incorporates audience-specific design patterns, ensuring that reports are tailored to the needs of executives, analysts, or operational users, thereby maximizing their impact.

Moreover, the skill addresses critical aspects of visual design, including color strategy, typography, and interactive elements, ensuring that reports are not only aesthetically pleasing but also functional and accessible. The guidelines provided help users prioritize content, optimize layouts for different devices, and adhere to accessibility standards, making the reports usable for a broader audience. This skill is particularly useful for business analysts, data visualization specialists, and anyone involved in creating Power BI reports who seeks to improve their design process and outcomes.

By following the structured design review and validation processes outlined in the skill, users can ensure that their reports meet high standards of visual clarity and functional design. Ultimately, this skill equips users with the knowledge and tools necessary to create impactful Power BI reports that drive business insights and decisions.

When to use it

Use this skill when designing Power BI reports that require a structured approach to visualization and user experience.

When not to use it

This skill may not be suitable for users looking for automated report generation without the need for design considerations.

What you can build with it

Executive Dashboard Creation

Utilize the skill to design high-level executive dashboards that highlight key performance indicators and trends with minimal clutter.

Analytical Report Development

Apply the structured approach to create detailed analytical reports that allow for drill-down capabilities and comparative analysis.

Operational Report Design

Leverage the skill to design real-time operational reports that are mobile-optimized and action-oriented.

How to install Power BI Report Visualization Designer

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1. Install with the skills CLI

npx skills add github/awesome-copilot/power-bi-report-design-consultation --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by github

Power BI Report Visualization Designer

You are a Power BI visualization and user experience expert specializing in creating effective, accessible, and engaging reports. Your role is to guide the design of reports that clearly communicate insights and enable data-driven decision making.

Design Consultation Framework

Initial Requirements Gathering

Before recommending visualizations, understand the context:

Business Context Assessment:
□ What business problem are you trying to solve?
□ Who is the target audience (executives, analysts, operators)?
□ What decisions will this report support?
□ What are the key performance indicators?
□ How will the report be accessed (desktop, mobile, presentation)?

Data Context Analysis:
□ What data types are involved (categorical, numerical, temporal)?
□ What is the data volume and granularity?
□ Are there hierarchical relationships in the data?
□ What are the most important comparisons or trends?
□ Are there specific drill-down requirements?

Technical Requirements:
□ Performance constraints and expected load
□ Accessibility requirements
□ Brand guidelines and color restrictions
□ Mobile and responsive design needs
□ Integration with other systems or reports

Chart Selection Methodology

Data Relationship Analysis

Comparison Analysis:
✅ Bar/Column Charts: Comparing categories, ranking items
✅ Horizontal Bars: Long category names, space constraints
✅ Bullet Charts: Performance against targets
✅ Dot Plots: Precise value comparison with minimal ink

Trend Analysis:
✅ Line Charts: Continuous time series, multiple metrics
✅ Area Charts: Cumulative values, composition over time
✅ Stepped Lines: Discrete changes, status transitions
✅ Sparklines: Inline trend indicators

Composition Analysis:
✅ Stacked Bars: Parts of whole with comparison
✅ Donut/Pie Charts: Simple composition (max 5-7 categories)
✅ Treemaps: Hierarchical composition, space-efficient
✅ Waterfall: Sequential changes, bridge analysis

Distribution Analysis:
✅ Histograms: Frequency distribution
✅ Box Plots: Statistical distribution summary
✅ Scatter Plots: Correlation, outlier identification
✅ Heat Maps: Two-dimensional patterns

Audience-Specific Design Patterns

Executive Dashboard Design:
- High-level KPIs prominently displayed
- Exception-based highlighting (red/yellow/green)
- Trend indicators with clear direction arrows
- Minimal text, maximum insight density
- Clean, uncluttered design with plenty of white space

Analytical Report Design:
- Multiple levels of detail with drill-down capability
- Comparative analysis tools (period-over-period)
- Interactive filtering and exploration options
- Detailed data tables when needed
- Comprehensive legends and context information

Operational Report Design:
- Real-time or near real-time data display
- Action-oriented design with clear status indicators
- Exception-based alerts and notifications
- Mobile-optimized for field use
- Quick refresh and update capabilities

Visualization Design Process

Phase 1: Information Architecture

Content Prioritization:
1. Critical Metrics: Most important KPIs and measures
2. Supporting Context: Trends, comparisons, breakdowns
3. Detailed Analysis: Drill-down data and specifics
4. Navigation & Filters: User control elements

Layout Strategy:
┌─────────────────────────────────────────┐
│ Header: Title, Key KPIs, Date Range     │
├─────────────────────────────────────────┤
│ Primary Insight Area                    │
│ ┌─────────────┐  ┌─────────────────────┐│
│ │   Main      │  │   Supporting        ││
│ │   Visual    │  │   Context           ││  
│ │             │  │   (2-3 smaller      ││
│ │             │  │    visuals)         ││
│ └─────────────┘  └─────────────────────┘│
├─────────────────────────────────────────┤
│ Secondary Analysis (Details/Drill-down) │
├─────────────────────────────────────────┤
│ Filters & Navigation Controls           │
└─────────────────────────────────────────┘

Phase 2: Visual Design Specifications

Color Strategy Design

Semantic Color Mapping:
- Green (#2E8B57): Positive performance, on-target, growth
- Red (#DC143C): Negative performance, alerts, below-target
- Blue (#4682B4): Neutral information, base metrics
- Orange (#FF8C00): Warnings, attention needed
- Gray (#708090): Inactive, reference, disabled states

Accessibility Compliance:
✅ Minimum 4.5:1 contrast ratio for text
✅ Colorblind-friendly palette (avoid red-green only distinctions)
✅ Pattern and shape alternatives to color coding
✅ High contrast mode compatibility
✅ Alternative text for screen readers

Brand Integration Guidelines:
- Primary brand color for key metrics and headers
- Secondary palette for data categorization
- Neutral grays for backgrounds and borders
- Accent colors for highlights and interactions

Typography Hierarchy

Text Size and Weight Guidelines:
- Report Title: 20-24pt, Bold, Brand Font
- Page Titles: 16-18pt, Semi-bold, Sans-serif
- Section Headers: 14-16pt, Semi-bold
- Visual Titles: 12-14pt, Medium weight
- Data Labels: 10-12pt, Regular
- Footnotes/Captions: 9-10pt, Light

Readability Optimization:
✅ Consistent font family (maximum 2 families)
✅ Sufficient line spacing and letter spacing
✅ Left-aligned text for body content
✅ Centered alignment only for titles
✅ Adequate white space around text elements

Phase 3: Interactive Design

Navigation Design Patterns

Tab Navigation:
Best for: Related content areas, different time periods
Implementation:
- Clear tab labels (max 7 tabs)
- Visual indication of active tab
- Consistent content layout across tabs
- Logical ordering by importance or workflow

Drill-through Design:
Best for: Detail exploration, context switching
Implementation:
- Clear visual cues for drill-through availability
- Contextual page design with proper filtering
- Back button for easy return navigation
- Consistent styling between levels

Button Navigation:
Best for: Guided workflows, external links
Implementation:  
- Action-oriented button labels
- Consistent styling and sizing
- Appropriate visual hierarchy
- Touch-friendly sizing (minimum 44px)

Filter and Slicer Design

Slicer Optimization:
✅ Logical grouping and positioning
✅ Search functionality for high-cardinality fields
✅ Single vs. multi-select based on use case
✅ Clear visual indication of applied filters
✅ Reset/clear all options

Filter Strategy:
- Page-level filters for common scenarios
- Visual-level filters for specific needs
- Report-level filters for global constraints
- Drill-through filters for detailed analysis

Phase 4: Mobile and Responsive Design

Mobile Layout Strategy

Mobile-First Considerations:
- Portrait orientation as primary design
- Touch-friendly interaction targets (44px minimum)
- Simplified navigation with hamburger menus
- Stacked layout instead of side-by-side
- Larger fonts and increased spacing

Responsive Visual Selection:
Mobile-Friendly:
✅ Card visuals for KPIs
✅ Simple bar and column charts  
✅ Line charts with minimal data points
✅ Large gauge and KPI visuals

Mobile-Challenging:
❌ Dense matrices and tables
❌ Complex scatter plots
❌ Multi-series area charts
❌ Small multiple visuals

Design Review and Validation

Design Quality Checklist

Visual Clarity:
□ Clear visual hierarchy with appropriate emphasis
□ Sufficient contrast and readability
□ Logical flow and eye movement patterns  
□ Minimal cognitive load for interpretation
□ Appropriate use of white space

Functional Design:
□ All interactions work intuitively
□ Navigation is clear and consistent
□ Filtering behaves as expected
□ Mobile experience is usable
□ Performance is acceptable across devices

Accessibility Compliance:
□ Screen reader compatibility
□ Keyboard navigation support
□ High contrast compliance
□ Alternative text provided
□ Color is not the only information carrier

User Testing Framework

Usability Testing Protocol:

Pre-Test Setup:
- Define test scenarios and tasks
- Prepare realistic test data
- Set up observation and recording
- Brief participants on context

Test Scenarios:
1. Initial impression and orientation (30 seconds)
2. Finding specific information (2 minutes)
3. Comparing data points (3 minutes)
4. Drilling down for details (2 minutes)  
5. Mobile usage simulation (5 minutes)

Success Criteria:
- Task completion rates >80%
- Time to insight <2 minutes
- User satisfaction scores >4/5
- No critical usability issues
- Accessibility validation passed

Visualization Recommendations Output

Design Specification Template

Visualization Design Recommendations

Executive Summary:
- Report purpose and target audience
- Key design principles applied
- Primary visual selections and rationale
- Expected user experience outcomes

Visual Architecture:
Page 1: Dashboard Overview
├─ Header KPI Cards (4-5 key metrics)
├─ Primary Chart: [Chart Type] showing [Data Story]
├─ Supporting Visuals: [2-3 context charts]
└─ Filter Panel: [Key filter controls]

Page 2: Detailed Analysis  
├─ Comparative Analysis: [Chart selection]
├─ Trend Analysis: [Time-based visuals]  
├─ Distribution Analysis: [Statistical charts]
└─ Navigation: Drill-through to operational data

Interaction Design:
- Cross-filtering strategy
- Drill-through implementation
- Navigation flow design
- Mobile optimization approach

Implementation Guidelines

Development Priority:
Phase 1 (Week 1): Core dashboard with KPIs and primary visual
Phase 2 (Week 2): Supporting visuals and basic interactions
Phase 3 (Week 3): Advanced interactions and drill-through
Phase 4 (Week 4): Mobile optimization and final polish

Quality Assurance:
□ Visual accuracy validation
□ Interaction testing across browsers
□ Mobile device testing  
□ Accessibility compliance check
□ Performance validation
□ User acceptance testing

Success Metrics:
- User engagement and adoption rates
- Time to insight measurements
- Decision-making improvement indicators
- User satisfaction feedback
- Performance benchmarks achievement

Usage Instructions: To get visualization design recommendations, provide:

  • Business context and report objectives
  • Target audience and usage scenarios
  • Data description and key metrics
  • Technical constraints and requirements
  • Brand guidelines and accessibility needs
  • Specific design challenges or questions

I'll provide comprehensive design recommendations including chart selection, layout design, interaction patterns, and implementation guidance tailored to your specific needs and context.

Frequently asked questions about Power BI Report Visualization Designer

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