Purpose Statement

This feature allows users to create Summary Reports that provide broad analytical views of totals, averages, trends, and percentages from agency data. Summary grouping transforms detailed records into meaningful aggregated insights that can be used for performance analysis, trend identification, and creating custom graphs or charts for presentations and decision-making.

Background Information

Summary grouping is specifically designed for Summary Report types in the Ad-Hoc reporting system and is accessed after completing data source configuration, column selection, sorting, and criteria filtering. Unlike tabular reports that display individual records, summary reports aggregate data into calculated totals, averages, counts, and other statistical measures. This feature is essential for executive dashboards, performance metrics, compliance reporting, and operational analysis. Summary reports can include row groups for categorical organization, summary columns for calculations, computed columns for advanced formulas, column groups for cross-tabulation analysis, and integrated charts for visual representation.

Required Permissions

Users must have access to the Reports Module and Ad-Hoc reporting functionality. Specific permissions are required based on the data sources and fields being summarized. Contact your system administrator if you encounter access restrictions when creating summary reports or accessing certain data fields.

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Step-by-Step Guide

Setting Up Row Groups

1. Navigate to the Summary Grouping tab after completing previous report configuration steps
2. Click the plus icon to add your first Row Group
3. Select any Data Field from your Data Source Configuration to group your data by (e.g., Shift, Department, Apparatus)
4. Optional: Click the plus icon again to add a second Row Group for nested grouping
5. Use the trash can icon to remove any unwanted groups
   

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Single Row Group Result: Creates one line item for each unique value in the selected field (e.g., one row each for Shift A, B, and C)

Multiple Row Groups Result: Creates a hierarchical structure with expandable/collapsible sections showing secondary groups nested within primary groups

Configuring Summary Columns

6. In the Summary Columns section, configure your data calculations:
   

• Count (number of records)
• Sum (total of numeric values)
• Average (mean of numeric values)
• Maximum (highest value)
• Minimum (lowest value)
  

B. Column for Aggregation: Choose which data field the calculation will be performed on

• Any field from your original Data Source is available
• Calculation options vary based on field type (numeric vs. text)

C. Filter Conditions: Apply additional filtering specific to this summary column

• Works independently of report-wide criteria filtering
• Allows different filters for multiple summary columns
• Example: Column 1 counts ALS calls, Column 2 counts BLS calls

D. Name: Enter a descriptive column header (e.g., "Calls per Shift")

E. Value Format: Select appropriate formatting for your calculation results:

• Number, Currency, Percentage, etc.
  

F. Decimals: Specify decimal places to display (0 for counts, 2 for currency)

G. Alias: System-generated identifier used for computed column formulas

Creating Computed Columns (Advanced Calculations)

7. Use Computed Columns to perform calculations based on Summary Column results:
   

A. Formula Creation:

• Use the dropdown to select column aliases for your formula
• Include mathematical operators: +, -, *, /
• Example formulas:
  • col_1 / col_1_total * 100 (calculates percentage of total)
  • col_1 + col_2 (adds two columns together)
    

C. Name: Provide descriptive name for the computed result

D. Value Format: Choose display format (Percent, Currency, Number, etc.)

Adding Column Groups (Cross-Tabulation)

8. Create Column Groups for more granular data breakdown:
   

A. Data Source Field: Select the field to group columns by

B. Calculation Type: Choose the measurement method for the grouped data

C. Data Source: Select the field to calculate against

Result: Transforms simple row-based reports into cross-tabulated data showing intersections of row and column groups

Adding Charts for Visualization

9. Create integrated charts for visual data representation:
   

A. Chart Type Selection:

• Bar: Horizontal bar graph
• Column: Vertical bar graph
• Donut: Circular chart without center
• Gauge: Progress gauge based on total goal
• Line: Connected data points showing trends
• Pie: Circular chart with data as wedges

B. Grouping: Select the Data Source Field from your Row Group configuration

C. Measure: Choose calculation method for chart data

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Chart Interaction: Hover over chart elements to display specific values and percentages

Best Practices

Do:

• Start with simple row groups before adding complexity
• Use meaningful names for summary columns that clearly describe the calculation
• Choose appropriate value formats and decimal places for your data type
• Test computed column formulas with sample data before finalizing
• Consider your audience when selecting chart types
• Use column groups for cross-tabulation analysis when comparing multiple dimensions

Don't:

• Create too many nested row groups (limits readability)
• Use complex computed formulas without documenting the calculation logic
• Apply conflicting filters that result in empty summary columns
• Choose inappropriate chart types for your data (e.g., pie charts for too many categories)
• Forget to set appropriate decimal places for different data types

Optimization Tips:

• Group by fields with manageable numbers of distinct values
• Use computed columns to create percentages and ratios for better analysis
• Combine multiple summary columns with different filters for comparative analysis
• Select chart types that best communicate your data story

Troubleshooting & FAQs

Q: My row groups aren't displaying any data. What's wrong? A: Ensure you have configured at least one Summary Column with appropriate measure and aggregation settings.

Q: Can I use the same field for both row groups and column groups? A: Yes, but this may create redundant information. Consider using different fields for more meaningful cross-tabulation.

Q: My computed column formula shows an error. How do I fix it? A: Verify that all column aliases in your formula exist and are spelled correctly. Ensure mathematical operators are valid.

Q: What's the difference between criteria filtering and summary column filtering? A: Criteria filtering applies to the entire report, while summary column filtering applies only to that specific column's calculation.

Q: Can I export summary reports with charts? A: Chart functionality depends on your export format. Contact your system administrator for specific export capabilities.

Q: How do I create percentage calculations? A: Use computed columns with formulas like col_1 / col_1_total * 100 and set the value format to "Percent."

Use Case Examples

Call Volume Analysis by Shift:

• Row Group: Shift (A, B, C)
• Summary Column: Count of Incident IDs
• Result: Total calls handled per shift

Apparatus Performance with Cross-Tabulation:

• Row Group: Shift
• Column Group: First Arriving Apparatus
• Summary Column: Count of Incidents
• Result: Calls per shift broken down by responding apparatus

Training Completion Rates:

• Row Group: Department
• Summary Column 1: Count of Completed Training (filtered)
• Summary Column 2: Count of Total Training Required
• Computed Column: (Completed/Total) * 100 for completion percentage

Revenue Analysis with Visualization:

• Row Group: Service Type (ALS, BLS, Transport)
• Summary Column: Sum of Billing Amount
• Chart: Pie chart showing revenue distribution by service type

Response Time Performance:

• Row Group: Incident Type
• Summary Column: Average Response Time
• Computed Column: Comparison to target response times
• Chart: Column chart showing performance against benchmarks

Advanced Features

Multi-Level Grouping:

• Primary groups create main categories
• Secondary groups create expandable subsections
• Use collapsible sections for detailed drill-down analysis

Cross-Tabulation Analysis:

• Combine row groups and column groups for matrix-style reports
• Ideal for comparing performance across multiple dimensions
• Useful for identifying patterns and correlations in data

Integrated Visualization:

• Charts automatically update based on grouping and summary configurations
• Multiple chart types available for different data presentation needs
• Interactive elements provide detailed information on hover