Client
localsearch
Tech stack
Google Cloud
Solution
Cloud Data Migration
Service
Data + Analytics
Accelerating to the Cloud: How Datatonic + localsearch Revolutionized Data Migration with Gemini
localsearch is a Swisscom company that provides local SMEs search and advertising services, with operations around the world. With a vision to become a true analytics and AI powerhouse, localsearch wanted to migrate its largest ERP and CRM data warehouse from on-premises Microsoft SQL Server (MSSQL) BI Stack to Google Cloud. localsearch used BigQuery Migration Service and Datatonic’s Gemini-powered GenAI accelerator to speed up the migration, rapidly unlock value from its data, and improve the services it offers to its customers.
Our impact
- Accelerated the migration to Google Cloud, using BigQuery Migration Service and Datatonic’s Gemini-powered Migration Accelerator
- Reduced load times for complex dashboards by 80% and time-to-data by 75% for faster analysis of ERP data, improving data-driven decision-making
- Reduced operational costs by migrating to BigQuery with a cost-elastic approach, decommissioning the previous cloud data warehouse solution
The challenge
As localsearch has scaled their business over time, the technology leadership wanted to reduce the complexity and cost of its data platform, and enable faster and improved data-driven decision-making to support this growth.
In a typical data modernisation project involving migration of data workloads into Google Cloud’s BigQuery, there are significant developer efforts required to ensure accurate, efficient and trustworthy migrations of data, SQL transformations, tests and associated metadata.
With their new lakehouse in BigQuery, localsearch aimed to migrate and then modernise data transformation and data quality automated tests with modern, cloud-native tools and services such as Google Cloud Dataform and Dataplex, thus enabling faster and more efficient access to data across the business.
Our solution
localsearch collaborated with Datatonic to migrate its existing on-prem Data Warehouse systems into Google Cloud, including support with design and full migration, and post-migration maintenance.
- Solution Design: Analysed current localsearch’s state in SQL Server and designed a solution, identifying priority use cases for an accelerated end-to-end platform build for faster migration to BigQuery.
- MVP Implementation: Productionised the MVP use cases and corresponding data models, integrating with source systems and developing further automation, security and governance. This included a comprehensive UAT stage.
- Scale Out: Scaled the new solution to migrate remaining use cases, data models and ETL pipelines to Google Cloud.
“With Datatonic’s help, we didn’t just migrate, but built a future-proof data platform. It enables lean management, unlocks real-time insights, powers (Gen)AI use cases, and is one we’re truly proud of.” – Markus Beck, Head of Data Insights, localsearch
Accelerating the migration
Whilst Google Cloud’s BigQuery Migration Service (BQMS) translation service allowed localsearch to have the legacy dialect already converted to BigQuerySQL, there’s still a significant effort required to have these transformations into Dataform models.
With Datatonic’s Gemini-powered Accelerator, we were able to significantly expedite the translated SQL to Dataform code conversion, by developing a GenAI-infused workflow. Building and then using the accelerator enabled us to accelerate the migration by an estimated additional 20% and in many cases, would allow complex legacy business logic that have been built over many years to be migrated to BigQuery + Dataform in a matter of weeks.
“Datatonic’s team made the migration journey collaborative and even fun. Their ability to blend deep technical expertise with creative problem-solving gave us confidence from day one.” – Alexandru Strimbeanu, Lead Cloud Data Engineer, localsearch
