Don’t Trust ETL Pipelines Without Automated Testing?
iceDQ automates end-to-end ETL testing to ensure data accuracy, completeness, and consistency at every stage. It validates transformations, detects mapping errors, and tests billions of records without sampling or manual effort, delivering 100% data reliability.
End-to-End automation of ETL testing designed for complex ETL data pipelines.
Connect and validate data across source, staging, and target systems, whether on-premise or cloud, using iceDQ’s 150 plus ready-to-use connectors.
iceDQ’s powerful ETL validation capabilities allow you to handle complex test logic across any source or target system.
Design complex scenarios and validations to detect rare edge cases and data mismatches that traditional sampling methods miss.
Trigger automated ETL testing in your CI/CD pipeline using API-first design and connect with tools like Jenkins or Git.
Automatically generate rules across thousands of tables and columns to ensure full coverage with minimal setup.
Reuse test cases across dev, QA, and production environments to standardize ETL QA and speed up ETL regression testing cycles.
Accelerate Testing with Prebuilt ETL Data Quality Checks
Runs complex test conditions using custom expressions.
Validates for NULLs, spaces, or
empty values.
Verifies if the attribute contains only the specified list of values.
Checks if the string value can be cast to a specific data type.
Ensures values fall within a specified range.
Validates string values against selected date formats
Matches values against a defined regular expression.
Detects duplicates based on a combination of one or more attributes.
Checks the length of each attribute value.
âWe have standardized iceDQ for all our cloud migration.â
âWe probably saved 5000 hours ($500,000) on the Data Migration Project.â
âBMC was able to achieve 100% test coverage after iceDQ implementation.â
âRuleGen utility helped Pfizer reduce the duration of IT testing from 24 months to 2 months.â
âiceDQ has enabled testers to keep up with the pace of developers. And reduced the testing time by half.â
âNot only did we achieve near perfect quality, but we also saved time and money on the project.â
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