Data Visualization and Dashboards

  1. Common Pitfalls and Best Practices
    1. Avoiding Misleading Visualizations
      1. Truncated Y-Axes
        1. When to Use
          1. Risks and Alternatives
            1. Clear Labeling
            2. Inappropriate Chart Types
              1. Misaligned Data and Chart
                1. Chart Selection Guidelines
                2. Correlation vs Causation Fallacy
                  1. Identifying Spurious Relationships
                    1. Statistical Significance
                    2. Cherry-Picking Data
                      1. Ensuring Data Completeness
                        1. Transparent Methodology
                        2. Scale Manipulation
                          1. Consistent Scales
                            1. Proportional Representations
                          2. Preventing Information Overload
                            1. Chart Junk Elimination
                              1. Removing Non-Essential Elements
                                1. Tufte's Principles
                                2. Data-to-Ink Ratio
                                  1. Maximizing Data Density
                                    1. Minimizing Decorative Elements
                                    2. Focusing on Essential Metrics
                                      1. Prioritizing Key Information
                                        1. Progressive Disclosure
                                        2. Cognitive Load Management
                                          1. Chunking Information
                                            1. Reducing Mental Effort
                                          2. Ensuring Data Accuracy and Trust
                                            1. Data Validation Processes
                                              1. Automated Checks
                                                1. Manual Review
                                                  1. Quality Metrics
                                                  2. Clearly Stating Data Sources and Timestamps
                                                    1. Source Attribution
                                                      1. Data Freshness Indicators
                                                        1. Update Frequencies
                                                        2. Handling Missing or Incomplete Data
                                                          1. Data Imputation
                                                            1. Visual Indicators for Missing Data
                                                              1. Transparency About Limitations
                                                              2. Error Handling
                                                                1. Graceful Degradation
                                                                  1. Error Messages
                                                                    1. Fallback Options
                                                                  2. Performance Optimization
                                                                    1. Query Optimization
                                                                      1. Efficient Data Retrieval
                                                                        1. Indexing Strategies
                                                                        2. Caching Strategies
                                                                          1. Client-Side Caching
                                                                            1. Server-Side Caching
                                                                            2. Data Aggregation
                                                                              1. Pre-Aggregated Views
                                                                                1. Summary Tables
                                                                                2. Lazy Loading
                                                                                  1. On-Demand Data Loading
                                                                                    1. Progressive Enhancement
                                                                                  2. Ethical Considerations
                                                                                    1. Representing Data without Bias
                                                                                      1. Avoiding Manipulative Visuals
                                                                                        1. Objective Presentation
                                                                                        2. Protecting Sensitive Information
                                                                                          1. Data Anonymization
                                                                                            1. Access Controls
                                                                                              1. Privacy Compliance
                                                                                              2. Transparency in Data and Design Choices
                                                                                                1. Documenting Assumptions
                                                                                                  1. Disclosing Limitations
                                                                                                    1. Methodology Transparency

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                                                                                                7. Advanced Dashboard Techniques

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                                                                                                9. Dashboarding Tools and Technologies