Datametica Enhances its Data Validation Technology – Pelican


Datametica, a data modernisation and cloud migration solution provider, added game-changing capabilities for its data validation technology, Pelican. Pelican has been simplifying data validation processes for years and has a proven track record. With its automated data validation capabilities, it has served hundreds of customers across various industries. The new Pelican is an enterprise-ready tool with significantly enhanced capabilities and AI automation approaches that further advance data validation functions, all with simple deployment options at a low cost.

The new Pelican has two modes of data validation: Litmus and Full mode. The enhanced Full mode of Pelican brings out all the mismatched cells in your data pipeline in a single iteration. Some of the new features that further automate the data validation process are:

  • AI-powered automated data validation & reconciliation
  • Lineage powered triaging
  • Built-in encryption and security features
  • Validation suite
  • Built-in reporting suite
  • CI/CD pipeline integration
  • Role-based access management
  • Enterprise ready tool
  • Parallel data validation
  • Zero coding requirement
  • Validation without data movement

With significant feature updates, the new Pelican comes at a compelling price. Pelican is now available with flexible payment options on both subscription and license models. Check the new Pelican pricing right now!

During the launch, Dr Phil Shelley, Co-founder and President of Datametica, said, “Pelican is already a state-of-the-art technology and is loved by our customers. Now new features, which further automate the data validation process and introduce AI capabilities, make it the most advanced data validation tool. We have also introduced new pricing for Pelican, making it affordable for wide adoption.”

Pelican – The Data Validator offers wide-ranging business and technology applications. Pelican reduces cost, time, and risk. It has applications in the following areas: Data migration and modernisation testing, production monitoring through KPIs, regression testing, data availability and disaster recovery testing, backup and restore, validation of data replication, ETL/data integration validation, and MDM testing.