Auto-Explain is a feature that automatically analyzes data variations and identifies root causes. It examines the underlying data structure to determine which factors contributed to a metric change between two data points.Documentation Index
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Atoti Intelligence Essentials
This is part of the Atoti Intelligence Essentials offer.What is Auto-Explain
Auto-Explain analyzes data to identify the root causes of variations. When a metric changes between two data points, Auto-Explain examines the underlying data structure to determine which factors contributed to the change. It provides:- Root cause members that contribute to the variation
- Contribution percentages for each factor
Why use Auto-Explain
Auto-Explain reduces the time spent investigating data variations manually. Key benefits include:- Identify root causes automatically
- Get clear explanations of metric changes
- Work with existing Atoti data models
- Focus analysis on relevant dimensions through configuration
Where to find Auto-Explain
Auto-Explain is available in the context menu of pivot tables in the Atoti UI after successful setup. To access it, right-click on a selected cell in a pivot table and select Auto-Explain from the context menu:
How to use Auto-Explain
Prerequisites
Before using Auto-Explain, ensure the following requirements are met:- Auto-Explain is set up in the project
- The Atoti application is running
- The Atoti UI is accessible
- A pivot table with data is available
Analyze a variation
Follow these steps to analyze a variation between two cells:- Open a pivot table in the Atoti UI
- Select two cells to compare
- Right-click one of the selected cells
- Select Auto-Explain from the context menu
- Wait for the analysis to complete

Interpret the results
The Auto-Explain results show:- Root cause members that contribute to the variation
- Contribution percentages for each factor
- Hierarchy levels where variations occur
Related reading
- Set up Auto-Explain to add the feature to a Java project
- Configure Auto-Explain to customize analysis behavior and adjust thresholds