Datametica Launched its SaaS-based Technology – Raven Code Conversion, on the Google Cloud Marketplace

Datametica, a leading data warehouse modernization and migration solution provider, launched its SaaS-based technology, Raven, on the Google Cloud Marketplace. Raven is a state-of-the-art code translation technology that converts workload from legacy data warehouses and ETL to native Google Cloud technologies. It saves time, and effort and reduces errors by rapidly transforming code of any length and complexity. Code such as SQL/scripts/ETLs are modernized to standardized and optimized target GCP technologies.

Raven greatly accelerates the modernization of legacy workloads to Google Cloud technologies, such as BigQuery. Raven also modernizes ETL such as DataStage, Informatica, SAS, and other solutions to GCP-native technologies.

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Google Cloud Marketplace enables customers to leverage software packages quickly and efficiently. Google Cloud customers, such as those migrating to Google BigQuery, can leverage Datametica SaaS-based technologies – Eagle, Raven, and Pelican, for an accelerated and safer cloud migration experience.

Following Raven technologies are available on Google Cloud Marketplace:

• DM-Raven-DDL
• DM-Raven-SQL-Views
• DM-Raven-NON-SQL
• DM-Raven-ETL
• DM-Raven-DAG creation

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During the launch of this event, Dr. Phil Shelley, Co-Founder and President of Datametica, said, “We are thrilled to announce the launch of this game-changing technology. Our goal has always been to simplify and accelerate the migration process and help businesses adopt GCP solutions. This new SaaS-based offering is a testament to our commitment to delivering innovative solutions that drive business success.”

“Moving beyond legacy infrastructure is crucial to keeping in lockstep with enterprise digital transformation efforts,” said Dai Vu, Managing Director, Marketplace at Google Cloud. “With workload transformations streamlined, as organizations can access Datametica’s Raven Code Conversion technology on Google Cloud Marketplace, accelerating the transition of workloads from legacy to modern infrastructure,” he added.

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