Case Study: world largest retailer achieves a 70% faster data processing with Tredence's Unified Customer Data Platform on Google Cloud

Helped a Global Retailer Develop a Unified Customer Data Platform on Google Cloud as a Foundation for Next Best Experience

The client, a world largest retailer, faced challenges with its fragmented and outdated Hadoop-based data infrastructure, which was unable to handle large volumes of customer data spread across disparate systems. Tredence partnered with the retailer to develop a Unified Customer Data Platform on Google Cloud, aiming to create a single source of truth and leverage AI/ML for improved customer strategies.

Tredence built an auto-scalable infrastructure on GCP, utilizing reusable data pipelines, BigQuery, and DataProc to manage variable workloads efficiently. This solution, which leveraged Kubeflow for model management, resulted in the platform processing 250 TB of data weekly. The retailer achieved a 70% reduction in processing time for computation-heavy jobs and cut overall costs by 30-35%.