Automate your ETL Data Testing and Validation using ETL Validator

The most comprehensive Data and ETL testing automation tool.

  • Automated ETL Testing
  • Data Comparison
  • Customizable Checks
  • Extensibility
  • Data Accuracy and Data Integrity
  • Early Error Detection
  • Trusted Reporting and Analytics
  • Alerts and Notifications
  • Version Control and Audit Trails
  • Easy Integrations and Plugin Supports

Benefits of ETL Validator

  • User Focused Low-Code / NO Code platform
  • Improved Data Quality with Time and Cost Savings
  • Scalability and Flexibility
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Why you should use ETL Validator?

    • An out-of-the-box wizards test case automation for data migration test cases and data-rule generation.
    • A template system for dataflows, test cases, data rules and pipelines for easy import, export, and easy integration system.
    • Zero-code and Low-code test-case generation are in place for quick and easy deployment without the need for technical know-how.
    • Built-in integration with AI systems and query builders for automation of transformation logic.
    • Existing Integrations with Data Warehouses, Cloud Solutions, Pipelines, and CICD tools.
    • Versatile connectors covering 99% of the data sphere with additional support for custom connections 
    • Automatic Data Observability systems for anomaly detection in data, metadata, and profiles. The application can keep track of data and its profiles over the course.
    • Supports SQL, Java, Scala, Python, Pyspark, DB Scripts and Shell Language for comfort of usage.
      • Automatic Default Reporting and Notification (with customizations for both) for all test-cases, rules, dataflows, and pipelines.  
      • Parameterization with Templates creates DQM pipelines and ETL Validation Systems that can be iteratively deployed in multiple environments.

    Key Features of ETL Validator

    • Automated ETL Testing: ETL Validator automates the testing process, reducing the need for manual intervention and streamlining ETL validation.
    • Data Comparison: It compares the data between the source and target systems, performing various checks to identify any inconsistencies or discrepancies.
    • Error Handling: ETL Validator identifies errors during the data transfer process and provides detailed information about the location and nature of the errors, facilitating efficient error handling.
    • Customizable Checks: The tool allows users to define custom validation rules and checks tailored to their specific ETL processes and data requirements. No restrictions are built into the application in terms of the creation of test cases and dataflows.
    • DB Metadata Testing: Helps audit changes to the metadata – data types, lengths, indexes. Simplifies comparison of database schema across environments.
    • Flat File Testing: Define rules for automatically validating data in each column in the incoming file. Has a built-in file watcher that automatically detects new files and kicks off tests.
    • Alerts and Notifications: ETL Validator generates alerts and notifications when errors are detected, ensuring that responsible parties are promptly informed about any issues.
    • Reporting and Analytics: It generates comprehensive reports with data validation results, helping users analyze the ETL process’s success and identify areas for improvement.
    • Data Masking: Some ETL Validator tools may offer data masking capabilities to anonymize sensitive data during the testing process, ensuring compliance with data privacy regulations.
    • Version Control and Audit Trails: ETL Validator may include version control and audit trail features to track changes to the ETL process and maintain a history of data validation activities.
    • Enterprise Collaboration: Capability to assemble and schedule test plans. Email notification, web reporting and ALM integration enables sharing of test results.
    • Visual Test Case Builder: A unique visual test case builder with drag & drop capabilities and a query builder that enables defining tests without manually typing in queries.
    • Data Quality Testing: Provides a data model driven interface for defining data rules to verify that the data conforms to quality standards and range of values.

    Automate your ETL Testing today!

    Experience the power of automated ETL and Datawarehouse testing with Datagaps ETL Validator and DataOps Suite.

    Schedule a demo or start your free trial today to see how DataOps Suite can transform your ETL/Datawarehouse testing processes.

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