Case Study: world's largest retailer achieves 70% faster turnaround and 30-35% cost savings with Tredence's GCP ML environment

World's Largest Retailer - Customer Case Study

The World's Largest Retailer, a leading global retailer, faced challenges with its fragmented and unscalable Hadoop-based infrastructure, which was unable to process its vast quantities of customer data. They engaged Tredence to create a more performant setup to reduce the time from data to insight and to leverage AI/ML for effective customer strategies.

Tredence implemented a petabyte-scale machine learning environment on Google Cloud Platform (GCP). The solution involved building reusable data pipelines, merging disparate data sources into a single source of truth, and using Kubernetes and Kubeflow for model management. The results for the retailer included processing 250 TB of data weekly, a 70% reduction in turnaround time for heavy computational jobs, and 30-35% overall cost savings.