Case Study: Leading US Retailing Company slashes licensing costs and accelerates large-volume data aggregation with Happiest Minds

Hadoop as ELT for Leading US Retailer

Happiest Minds helped a leading US retailer address rising analytics costs and performance bottlenecks by replacing part of a Teradata-centric pipeline. The retailer needed to cut license expenses, support large-volume aggregations, and make the change with minimal impact on existing reporting.

The team implemented a Hadoop-based ELT: Sqoop to extract data from Teradata, Hive for transformation and aggregation, and MongoDB as the central store for downstream reporting. The solution enabled efficient data migration, fast aggregation on very large datasets, and significantly lower licensing costs while preserving reporting continuity.