The Company:
A leading American home improvement retail giant with a nationwide footprint. This company is known for its wide selection of hardware, appliances, building materials, and home decor products, serving both DIY enthusiasts and professional contractors.
The Challenges:
The retail company recognized that their legacy Teradata data warehouse was hindering their ability to compete in a rapidly evolving retail landscape. They faced escalating maintenance costs and limits on their capacity to unlock the full potential of their data. To optimize inventory management, make smarter, data-driven decisions, and empower both customers and employees with self-service insights, the company needed a modern, scalable data platform. This transformation would not only address immediate cost concerns but also propel them into the future of data-driven retail.
The Solution
Onix deployed a strategic solution to accelerate the retailer’s migration to BigQuery, driving the achievement of their key business objectives, including:
- Successful BigQuery migration:Onix smoothly migrated 61 TB of historical data and approximately 1600 tables from Teradata to BigQuery.
- FinOps optimization:Onix’s recommendations for leveraging FinOps principles will help the home improvement retailer optimize cloud costs and modernize resources for even greater long-term benefits.
- Future-facing initiatives:The partnership has set the stage for an upcoming mainframe migration project, where legacy JCL scripts will be migrated to BigQuery, further streamlining the retailer’s data architecture.
Outcomes
This ambitious migration and modernization program will become a benchmark for the retail industry. By transitioning business users to cloud-based data consumption and accelerating application turnaround times, this initiative creates a foundation for rapid, AI-driven innovation. Onix’s role in this transformation is key: we’re not only streamlining the migration process with the Datametica Birds, reducing cycle time by up to 30%, but also unlocking long-term cost savings through the decommissioning of legacy Teradata systems. The result: tangible cost reductions, faster time-to-market for new products, and a data landscape optimized for innovation.
