Eagle Eye

Celebal Eagle Eye is an enterprise-grade data observability platform designed to ensure end-to-end data quality, transparency, and trust across modern data ecosystems. Developed by Celebal Technologies, the tool is built to run seamlessly on AWS , enabling organizations to quickly deploy and scale within their existing AWS infrastructure. It offers robust connectivity to diverse AWS-native data sources, including Amazon Redshift and Amazon S3, as well as other platforms such as Databricks and SQL Server, allowing teams to monitor and validate data pipelines efficiently.

Once connected, users can browse catalogs and schemas to select specific tables for profiling. The platform performs automated data quality checks at both the table and column levels, including validations for nulls, duplicates, freshness, schema drift, and data type mismatches. These checks are executed automatically upon table selection, without requiring manual triggers or configurations.

Eagle Eye provides intuitive dashboards that display overall data quality scores, along with deep-dive insights into individual tables and columns. Visual trend charts help track data health over time, enabling users to identify patterns, spot anomalies, and respond proactively. The tool also allows complete customization—users can enable or disable individual checks at any level, tailoring monitoring to specific business rules or technical requirements.

To further enhance user experience, Eagle Eye includes an intelligent chatbot interface that supports real-time root cause analysis (RCA) investigations, delivers table health summaries, raises tickets, shows ticket history, and even provides KPI-based insights through a dedicated KPI bot—making complex observability tasks conversational and accessible directly from chat platforms. To further enhance user experience, Eagle Eye includes an intelligent chatbot interface that supports real-time root cause analysis (RCA) investigations, delivers table health summaries, raises tickets, shows ticket history, and even provides KPI-based insights through a dedicated KPI bot—making complex observability tasks conversational and accessible directly from chat platforms.

The platform supports automated scheduling of profiling jobs, including daily profiling, eliminating the need for manual intervention and ensuring continuous data monitoring. For immediate checks, users can also perform on-demand profiling of specific tables directly from the UI.

Eagle Eye tracks and visualizes profiling job statuses—ongoing, completed, or failed along with execution durations, providing full visibility into job performance and system behavior.

To support rapid response and incident management, Eagle Eye integrates with AWS CloudWatch, AWS SNS, Jira, and Slack/Outlook and almost all atlassian tools, enabling real-time alerts and automated ticket generation for any detected data quality issues. These integrations help streamline issue resolution and maintain data reliability across operational workflows.

As a product, Eagle Eye combines observability, automation, flexibility, chatbot-driven operations, and enterprise-grade alerting into a single platform, making it an essential tool for enterprises aiming to maintain high data quality standards across large and complex data environments.