Stop Errors Before They Reach Production
iceDQ automates data warehouse testing at scale, validating billions of records in minutes with no sampling and no manual effort. It checks schema, row counts, reconciliations, and transformations across every stage of your ETL. Run data warehouse regression testing along with unit and functional tests, reuse test cases across environments, and ensure your data is always accurate before it hits production.
Effortlessly automate and scale your Data Warehouse testing with confidence.
Seamlessly connect and test data across cloud and on-premise data warehouses using iceDQ’s 150+ prebuilt connectors. Supports platforms such as Snowflake, Redshift, BigQuery, SQL Server, and more.
iceDQ’s powerful validation engine handles complex business logic and enables full test coverage across schema, row counts, transformations, and data reconciliations between any source and target.
Design robust scenarios that help detect edge cases and data mismatches often missed by traditional sampling methods. iceDQ tests 100 percent of the data, leaving no blind spots.
Accelerate testing using prebuilt rule templates for completeness checks, null values, data patterns, date validations, and more. No coding required.
Use AI-driven rule generation to automatically create validation logic across all rows, columns, and tables. Reduce manual setup and improve test coverage instantly.
Reuse test suites across development, QA, staging, and production environments to ensure consistency and speed up regression testing cycles.
Accelerate Testing with Prebuilt Data Reliability 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.
“We have standardized iceDQ for all our cloud migration.”
“We probably saved 5000 hours ($500,000) on the Data Migration Project.”
“BMC was able to achieve 100% test coverage after iceDQ implementation.”
“RuleGen utility helped Pfizer reduce the duration of IT testing from 24 months to 2 months.”
“iceDQ has enabled testers to keep up with the pace of developers. And reduced the testing time by half.”
“Not only did we achieve near perfect quality, but we also saved time and money on the project.”
Our team would love to hear from you.
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