We’re excited to announce two major expansions to DataOps Data Quality TestGen Enterprise that bring intelligent data quality testing to even more of your data ecosystem. Whether you’re working with Google BigQuery or managing file-based data through external tables, TestGen now has you covered.
Google BigQuery Support: Enterprise-Grade Testing Meets Cloud Data Warehousing
DataOps TestGen Enterprise is now fully compatible with Google BigQuery, one of the most popular cloud data warehouse solutions. This integration means you can now apply the same rigorous data quality standards to your BigQuery datasets that you’ve come to expect from TestGen.
What this means for your team:
With BigQuery support, TestGen offers advanced profiling features that automatically analyze the structure, patterns, and anomalies in your BigQuery tables. The platform generates detailed test suites automatically, eliminating the manual effort typically required to establish data quality benchmarks. Setting up TestGen with BigQuery is straightforward, allowing you to quickly gain insights into database health, identify potential data issues before they impact downstream processes, and maintain confidence in your analytics and machine learning workflows.
File-Based Data and Apache Iceberg: A New Level of Architectural Independence
Perhaps even more exciting is TestGen’s expanded support for file-based data formats. DataOps TestGen Enterprise can now profile and test structured data stored in file formats and accessed through Redshift Spectrum and Snowflake Amazon Redshift Spectrum and Snowflake external tables
external tables. Supported formats include: Apache Iceberg tables, Parquet, Avro, ORC, CSV, JSON
Why this matters
This capability marks a paradigm shift for data architects. You’re no longer limited to testing only data within traditional database systems. Whether you’re building a data lakehouse architecture, working with data lake storage, or managing data in modern table formats like Apache Iceberg, DataOps TestGen can now verify quality at the source
This architectural flexibility allows you to perform data quality checks earlier in your pipeline, detect issues before data reaches your warehouse, and ensure consistency across hybrid storage strategies. For organizations adopting data lake and lakehouse architectures, this offers enterprise-grade testing for your most flexible storage layers.
Getting Started
Ready to expand your data quality coverage? Refer to the Introduction to DataOps TestGen for a comprehensive list of supported databases and setup instructions.
These new integrations reflect our commitment to meeting data teams where they are—regardless of which databases, warehouses, or storage formats power your data infrastructure. Whether you’re fully invested in BigQuery, building a modern lakehouse, or operating a hybrid environment, TestGen helps ensure your data is reliable, trustworthy, and ready to inform critical business decisions. Today, v4.32.5 of Enterprise TestGen supports these features. Open source will follow soon!
Want to learn more about how TestGen can improve data quality in your organization? Visit our website for an online demo.
