#data validation testing tools

[onixcloud]

Pelican: AI-Powered Automated Data Validation Tool by Onix

Validate enterprise data at scale with Pelican by Onix—an AI-enabled, zero-code data validation & reconciliation tool. No data movement. No

Migrate your data with confidence using Pelican by Onix, a cutting-edge data validation tool designed to ensure complete accuracy during cloud transformations. As an automated data validation tool, Pelican identifies inconsistencies, reconciles data, and preserves business logic across SQL, ETL, and BI workloads in real time. Trusted among top data validation testing tools, it offers rapid test creation, six-point quality checks, and near-zero error rates — all without moving a single byte. Deliver reliable, high-quality data faster and empower your enterprise analytics with Pelican by Onix.

[datameticasols]

Revolutionizing Data Validation with AI-Powered Cell-Level Full Validation

Unlock data accuracy with Pelican’s Full Data Validation. Discover how this AI-powered tool revolutionizes cell-level data validation in a s

Datametica’s blog underscores the importance of cell‑level data validation in today’s data‑driven world. It explains that ensuring data accuracy and integrity is essential to avoid costly errors and maintain trust. The article highlights how cell‑level validation preserves data integrity, prevents errors, enhances quality, meets regulatory compliance, and supports better decision‑making. It notes that traditional data validation testing tools are often manual and iterative, making them impractical for complex modern data pipelines.

To overcome these challenges, Datametica introduces Pelican, an AI‑powered data validation tool. Pelican’s Full Validation feature identifies all mismatched cells in a single iteration, handles diverse load and table types, and reduces validation time and resource consumption, delivering cost savings on cloud platforms. By automating cell‑level checks, Pelican minimizes QA effort and helps businesses improve data quality and decision‑making. The article positions Datametica as a global leader in data warehouse modernization and migration, helping organizations move data and workloads to the cloud using automation. Pelican is presented as a game‑changing data validation tool for modern businesses seeking efficient and comprehensive data validation.

[datameticasols]

Ensuring Data Integrity in Disaster Recovery with Automation

Safeguard data integrity during disaster recovery with automated data validation using Datametica's Pelican. Ensure reliability, compliance,

When disaster strikes, restoring your data isn’t enough — you need to validate that every piece is accurate, complete, and production-ready.

In our latest blog, Datametica explores how automation is transforming disaster recovery, with tools that verify data integrity without manual intervention.

At the heart of our approach is Pelican, an AI-powered automated data validation tool that compares, reconciles, and certifies datasets at scale — across environments like production, DR, and backup.

Unlike traditional data validation testing tools, Pelican works with APIs, has built-in scheduling, and performs intelligent checks down to the cell level — without needing to move or recode your data.

Want true confidence in your DR processes? See how Datametica is redefining trust in cloud data operations.

[onixcloud]

Cisco Enhances Security and Efficiency with Automated Data Validation Tools

Cisco successfully leveraged Pelican, a cutting-edge data validation tool, to enhance security and efficiency in its internal migration initiative. By implementing an automated data validation tool, Cisco eliminated manual validation, ensuring 100% secure data validation without data movement. This transformation resulted in zero test failure rate, validation of over 2 trillion rows, and organization-wide adoption, empowering 150+ data engineers. The collaboration between Cisco and Onix showcased the power of scalable data validation solutions, setting a new benchmark for data integrity and validation testing in large enterprises.

Click: https://www.onixnet.com/case-study/cisco-leverages-pelican-for-100-secure-data-validation/

[icedq-toranainc]

iCEDQ for ETL Testing -  Big Data Lakes Data Warehouses

ETL Testing is a process enabling a user to test by validating and comparing source data to destination data. With iCEDQ ensure quality checks to maintain the consistency of both data and business KPIs. To know more about the iCEDQ's ETL testing tool or request a demo. Visit: https://bit.ly/3iDzE93

[etl-testing-tools]

This article discusses why and how to use both together, and dives into the challenges of Bulk Data Migration to Snowflake. Why and How? People are rapidly adopting cloud architectures for Data Warehouses and Machine Learning projects due to the economies of scale in the cloud. One obstacle in achieving rapid success is the data […]

People are rapidly adopting cloud architectures for Data Warehouses and Machine Learning projects due to the economies of scale in the cloud. One obstacle in achieving rapid success is the data and data types inconsistencies between on-premise structures and the modern data stacks in the cloud.

When you migrate vast amounts of data to the cloud, the opportunity to introduce mistakes is multiplied due to these reasons and others. The earlier you catch the issues, the less costly it is to resolve the discrepancies.