Power BI Development Constraints

When building visualizations and dashboards in Power BI, you'll encounter several constraints that may limit what you can accomplish. Understanding these limitations will help you design more effective solutions within the platform's capabilities.

Data and Performance Constraints

1. Data Size Limitations:

   • Power BI Desktop has a 10 GB compressed data model size limit
   • Power BI Service (cloud) has varying limits based on your license (1 GB for free, 10 GB for Pro, 100 GB for Premium)
   • DirectQuery mode can help with large datasets but introduces performance trade-offs

2. Row Limits:

   • Visual-level row limit of approximately 30,000 data points per visual
   • Importing more than 100 million rows can cause significant performance issues

3. Refresh Limitations:

   • Free tier: Daily refresh limit
   • Pro license: 8 refreshes per day
   • Premium: 48 refreshes per day
   • Minimum refresh interval: 30 minutes (15 minutes in Premium)

Visual and Design Constraints

1. Custom Visual Limitations:

   • Custom visuals may have performance issues with large datasets
   • Some custom visuals lack advanced formatting options
   • Custom visuals may break with Power BI updates

2. Layout Constraints:

   • Limited pixel-perfect positioning compared to design tools
   • Fixed grid layout system with limited flexibility
   • Mobile view has additional layout constraints

3. Formatting Limitations:

   • Limited typography options and font choices
   • Conditional formatting has limited scope and complexity
   • Limited animation capabilities

Analytical Constraints

1. DAX Limitations:

   • Complex calculations can impact performance
   • No native support for certain statistical functions
   • Limited recursion capabilities

2. Time Intelligence Constraints:

   • Date tables required for proper time intelligence
   • Complex fiscal calendars can be challenging to implement
   • Limited support for non-standard time hierarchies

3. Relationship Limitations:

   • Maximum of 4 million relationships per model
   • No native many-to-many relationships (requires workarounds)
   • Bidirectional filtering can cause performance issues

Security and Sharing Constraints

1. Row-Level Security Limitations:

   • Complex RLS rules can impact performance
   • Limited dynamic security options in the free tier
   • Cannot use RLS with Analyze in Excel

2. Sharing Constraints:

   • Free tier: Cannot share with others
   • Pro license: Can only share with other Pro users
   • Limited embedding options without Premium capacity

Best Practices Within Constraints

1. Data Modeling:

   • Use star schema design
   • Minimize calculated columns in favor of measures
   • Implement aggressive filtering and aggregation

2. Visual Design:

   • Use built-in visuals when possible for better performance
   • Limit the number of visuals per page (5-7 maximum)
   • Use bookmarks and drill-through for complex navigation

3. Performance Optimization:

   • Implement query folding where possible
   • Use incremental refresh for large datasets
   • Monitor and optimize with Performance Analyzer

By understanding these constraints, you can design Power BI solutions that work effectively within the platform's capabilities while still delivering valuable insights to your users.

Power BI Vessel Price Dashboard Design

Based on Power BI's constraints, I've redesigned the vessel price visualization to work effectively within Power BI's capabilities while maintaining the ability to analyze all three dimensions (vessel age band, time, and vessel class).

Power BI Design Considerations

This redesign takes into account several Power BI constraints and best practices:

1. Visual Selection

• Used only standard visuals that are native to Power BI:

  • Line chart for time series data
  • Bar chart for comparison across vessel classes
  • Card visuals for KPIs
  • Table/matrix for detailed data and age band comparison

2. Layout Structure

• Implemented a grid-based layout similar to Power BI's canvas
• Used proper spacing and alignment that matches Power BI's layout system
• Designed with responsive considerations that work within Power BI's constraints

3. Color Scheme

• Used the default Power BI color palette:

  • Teal (#01B8AA) for Capesize
  • Dark gray (#374649) for Panamax
  • Red (#FD625E) for Supramax
  • Yellow (#F2C80F) for Handysize

4. Filtering Approach

• Added a filter bar at the top that mimics Power BI's filtering experience
• Simplified the filtering options to match what's easily achievable in Power BI

5. Data Visualization

• Focused on showing the relationship between the three dimensions:

  • Time dimension shown primarily in the line chart
  • Vessel class dimension shown across all visuals with consistent colors
  • Age band dimension shown in the matrix/table with values for each combination

6. Performance Considerations

• Limited the number of visuals to prevent performance issues
• Used simple visualizations that work well with larger datasets
• Avoided complex custom visuals that might cause performance problems

This design provides a practical approach that could be implemented in Power BI while still effectively visualizing the relationship between vessel age band, time, vessel class, and price.