Adeo Modernizes its Data Infrastructure with Datometry on Google BigQuery

SAN FRANCISCO , Oct 11, 2022 — Datometry, the database virtualization company, announced today that leading French home goods retailer Adeo has completed a key milestone of the modernization of its data infrastructure by migrating from its legacy data warehouse, Teradata, to Google Cloud’s BigQuery.

The largest DIY retailer in Europe and third largest in the world, has 150,000 employees and 1,000 retail shops in 20 countries that meet a range of home goods needs, including renovations, DIY, and décor. The company needed to move from its highly entrenched data system to BigQuery, wanting to do so without disrupting business users worldwide. Using the Datometry Hyper-Q virtualization platform – the industry’s first to make existing applications seamlessly interoperable with cloud databases – Adeo was able to deliver on a multi-project architecture leveraging BigQuery that serves users in multiple geographies simultaneously.

In a joint effort between Datometry, Google Cloud, Adeo, and Adeo’s service partners Sopra Steria and CGI, Adeo redesigned and implemented its ETL. Then, Datometry generated the mapping of over 200,000 database objects from Teradata to BigQuery, fully automatically. That set the stage for Adeo to virtualize the entire reporting and consumption layer using Datometry Hyper-Q. This approach made for a completely seamless transition so that Adeo’s business users around the world would not even know that their core data platform has been replaced with BigQuery.

“Adeo, a global leader in its industry, was acutely aware that a conventional database migration would come with significant disruptions to its business,” said Mike Waas, CEO, Datometry. “Therefore, together with Google Cloud, we delivered on a vision that empowered Adeo to adopt BigQuery as their new data warehouse platform faster than with any other methodology—and, notably, without disrupting the business.”

Datometry Hyper-Q uniquely addressed Adeo’s business objectives, enabling the company to transfer its existing applications natively to BigQuery without costly rewrites of SQL code, at a fraction of the time and risk associated with typical database migrations. Had Adeo chosen to rewrite and redesign their reporting layer instead of virtualizing it, Adeo would have faced additional expenses of millions of dollars over the course of several years, with no guarantee of success.

“When Google Cloud first introduced us to Datometry we were thrilled,” said Eric Foratier, Digital Domain Leader, Adeo. “Datometry enabled us to migrate at a highly accelerated pace and quickly unlock the benefits of Google Cloud. With Datometry Hyper-Q, we were able to implement a multi-project architecture that would have been close to impossible to build otherwise.”

“We’re proud to partner with Datometry and help Adeo along its digital transformation journey,” said Sudhir Hasbe, Sr. Director of Data Analytics, Google Cloud. “By migrating its data warehouse with Datometry to BigQuery, Adeo teams can access and leverage data insights at global scale, enabling elevated customer experiences for its end customers.”

Datometry Hyper-Q is used by leading Fortune 500 and Global 2000 enterprises to accelerate cloud modernization and move workloads between data warehouses. The Datometry Hyper-Q virtualization platform eliminates risk-laden, expensive, and time-consuming application rewrites. For more information, visit www.datometry.com.

About Datometry

Datometry is the global leader in database system virtualization. Datometry empowers enterprises to run their existing applications directly on the cloud database of their choice without the business disruption of costly and risk-laden database migrations and application rewrites. Leading Fortune 500 and Global 2000 enterprises worldwide realize significant cost savings and consistently outpace their competition by using Datometry during this critical period of transformation to cloud-native data management. For more information, visit www.datometry.com.

Source: Datometry