Automate Your Data Pipeline with iceDQ: ETL, Big Data, BI Reports, and More

Looking for an all-in-one platform to test and monitor your ETL, big data, BI reports, and data migration processes? iceDQ is a DataOps automation platform that streamlines your entire data pipeline—from development to production. Whether you’re validating complex transformations, reconciling massive data sets, or ensuring accuracy in live production environments, iceDQ has you covered.

Key Highlights

* ETL & Big Data Testing: Validate incoming files for nulls, data formats, and duplicates. Reconcile source and target data for accurate movement.
* BI Report Testing: Automate the verification of business-critical reports and dashboards against underlying databases.
* Data Migration: Certify legacy-to-cloud and other migrations, ensuring all data is moved accurately and consistently.
* Production Data Monitoring: Embed iceDQ in your live data pipeline to catch errors, stop problematic jobs if needed, and alert your team in real time.
* Proven Efficiency Gains: Increase productivity by 70%, expand test coverage by 200%, and reduce project timelines by 33%.

Eliminate data risks, maintain compliance, and drive on-time project delivery with iceDQ’s powerful rules engine and real-time monitoring capabilities.

Ready to transform your data operations?
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About iceDQ: Ensuring Reliable Data From Development to Production with iceDQ.

iceDQ is a one-stop platform for data reliability with unified data testing, monitoring, and observability. Large banks, insurance, healthcare, and other enterprises rely on iceDQ in both development and production environments, ensuring data reliability and robust processes.

Streamlined Data Testing in Development: iceDQ is used to automate data migration testing, ETL data pipeline testing, big data lake testing, BI report testing, and more. It helps identify and fix data issues early in the data development lifecycle.

Proactive Monitoring and Observability in Production: iceDQ is used by operations to establish checks and controls for their data pipelines, and the AI-based observability engine ensures anomalies are detected and incidents are reported.
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