🚨 Alert Rules Overview

Alert Rules provide a robust framework for creating automated subprocesses that analyze data within repositories based on predefined SQL queries or Knowledge Graph filters. This enables proactive monitoring to detect specific conditions or matches within your data. When such conditions are identified, alerts are triggered, and notifications are sent to designated platforms, including the web, email, and mobile apps, according to user session configurations.

🌟 Key Features

1. 🧑‍💻 SQL-Based Analysis
   Define SQL queries to specify conditions for data analysis, allowing precise detection of relevant matches or anomalies in the data.

2. 📊 Knowledge Graph-Based Analysis
   Establish filters based on columns in your Knowledge Graph to detect specific conditions effectively.

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   Learn More About Filters

   • Filters
   • How to Create a Filter

3. 🔔 Automated Notifications
   Automatically trigger alerts and notifications when conditions are met, ensuring timely awareness and response to critical events.

4. 📱 Multi-Platform Notifications
   Send notifications across various platforms, including web, email, and mobile apps. External applications such as Telegram, Discord, or Slack can also be integrated, enhancing communication flexibility.

5. 👥 Configurable User Sessions
   Customize alert configurations to align with user sessions and preferences, ensuring that notifications reach the right stakeholders at the right time.

💡 Benefits

Alert Rules simplify monitoring by automating the detection of critical conditions. By leveraging SQL queries, organizations can proactively identify anomalies, patterns, or events, enabling swift corrective actions and improving operational efficiency.

🔍 Use Cases

1. Real-Time Monitoring
   Monitor data streams in real time to detect anomalies or deviations from expected patterns.

2. Compliance Monitoring
   Set up alerts for specific data thresholds or conditions to ensure compliance with regulatory requirements.

Alert Rules empower organizations to stay ahead of potential issues, ensuring that critical events are detected and acted upon promptly, making your data operations more efficient and proactive.