Datagaps ETL Validator is a software tool designed to automate the testing and validation of ETL (Extract, Transform, Load) processes and data pipelines. It enables organizations to ensure data accuracy, completeness, and integrity as data moves between sources and targets, supporting both legacy and modern data platforms. The tool leverages a no-code/low-code interface, AI-powered data quality assessment, and robust integration capabilities to streamline ETL testing, reduce manual effort, and improve operational efficiency.

Key Features

Automated ETL Testing Automates validation of ETL and data migration processes.

• Compares billions of records between source and target systems
• Detects data inconsistencies and transformation errors

No-Code/Low-Code Test Creation Enables test case creation without extensive programming.

• Drag-and-drop visual builder and query builder
• Supports SQL, Python, and Scala for advanced transformations

AI-Powered Data Quality Assessment Uses AI to enhance data quality and testing efficiency.

• Gen AI integration for transformation testing and prompt-based test setup
• Agentic AI for automated test case generation

Broad Data Source Connectivity Connects to over 40 data sources and major file types.

• Supports Snowflake, Databricks, AWS S3, Google BigQuery, and more

Scalability and Performance Handles massive datasets with high performance.

• Powered by Apache Spark for auto-scaling
• Executes parallel test cases

Integration and Extensibility Integrates with data quality, governance, and workflow tools.

• API and JDBC connectivity
• 50+ plugins for ticketing, scheduling, notifications, and reporting7

Benefits

Improved Data Accuracy and Trust Ensures reliable data movement and transformation.

• Reduces risk of data errors and inconsistencies
• Supports compliance and audit requirements

Operational Efficiency Accelerates ETL testing and reduces manual workload.

• Bulk test case creation and automation
• Real-time reporting and notifications

Flexibility and Ease of Use Adapts to diverse data environments and user skill levels.

• No-code/low-code interface for non-programmers
• Custom rule deployment for complex validation needs