💡 AI Insights

Automatic anomaly detection, trend analysis, and intelligent recommendations powered by advanced AI algorithms.

Overview

AI Insights automatically analyzes your data to:

• Detect anomalies and outliers
• Identify trends and patterns
• Generate actionable recommendations
• Predict future outcomes
• Surface hidden correlations

Types of Insights

1. Anomaly Detection

Automatically identifies unusual data points:

• Statistical outliers
• Unexpected spikes or drops
• Pattern breaks
• Data quality issues

Example:

2. Trend Analysis

Identifies directional changes over time:

• Upward/downward trends
• Seasonal patterns
• Growth acceleration/deceleration
• Cyclical behavior

Example:

3. Correlation Discovery

Finds relationships between metrics:

• Positive/negative correlations
• Causal relationships
• Leading indicators
• Cross-metric patterns

Example:

4. Forecasting

Predicts future values:

• Time series predictions
• Confidence intervals
• Multiple scenarios
• Risk assessment

Example:

5. Segment Analysis

Identifies distinct groups in data:

• Customer segments
• Product categories
• Behavioral clusters
• Geographic patterns

Insights Dashboard

Recent Insights

View the latest findings:

• Sorted by severity and confidence
• Filter by type or data source
• Mark as read/unread
• Save important insights
• Share with team members

Insight Details

Click any insight to see:

• Detailed explanation
• Supporting data and visualizations
• Historical context
• Confidence score breakdown
• Recommended actions

Configuring Insights

Data Sources

Enable insights for specific databases:

1. Navigate to Insights Settings
2. Select data sources to analyze
3. Choose tables/metrics to monitor
4. Set analysis frequency

Sensitivity Levels

Control what gets flagged:

• High: Only major anomalies
• Medium: Balanced detection (default)
• Low: Catch everything, may have noise

Notification Preferences

Choose how to receive insights:

• Critical Only: High severity insights
• Daily Digest: Summary email once per day
• Real-time: Immediate notifications
• Weekly Report: Comprehensive weekly summary

Acting on Insights

Validate

Confirm the insight is accurate:

• Review supporting data
• Check confidence score
• Compare with domain knowledge
• Investigate root causes

Investigate

Dig deeper into findings:

• Run related queries
• View detailed metrics
• Check historical data
• Compare segments

Take Action

Respond to insights:

• Create tasks or tickets
• Schedule follow-up analysis
• Adjust business processes
• Update forecasts/plans

Provide Feedback

Help improve AI accuracy:

• Mark as helpful/not helpful
• Report false positives
• Suggest improvements
• Request specific analyses

AI Models Used

Insights leverage multiple AI techniques:

• Time Series Analysis: ARIMA, Prophet, LSTM
• Anomaly Detection: Isolation Forest, Z-score, IQR
• Clustering: K-means, DBSCAN
• Regression: Linear, Polynomial, Random Forest
• Classification: Decision Trees, SVM

Best Practices

• Review Regularly: Check insights dashboard daily
• Validate Before Acting: Don't blindly trust AI
• Provide Feedback: Helps improve accuracy
• Start with High Confidence: Focus on 80%+ insights first
• Document Findings: Keep notes on validated insights
• Share Key Insights: Distribute to stakeholders

Permissions

Required permissions:

• insights.read: View insights
• insights.create: Generate custom analyses
• insights.update: Configure settings