Case Study: Huq achieves real-time data flexibility and lower costs with Looker

Building a powerful data platform to deliver near real-time location data at scale

Huq, a UK technology company that uses first-party location data to measure footfall and provide near real-time economic insights, needed to migrate its data pipeline to Google Cloud while keeping its stack flexible, responsive, and cost-controlled. The company also wanted faster access to high-frequency data for customers and a way to manage growing usage without losing efficiency. Looker was part of the analytics reporting environment, with data also being delivered through dashboard-style outputs and reports.

Looker and the broader Google Cloud stack were implemented to support Huq’s real-time data workflows, while the vendor, DoiT International, helped optimize the migration with tools like reOptimize and superQuery for better BigQuery efficiency. DoiT also guided machine-type optimization, enabling Huq to build a pipeline that ingests, processes, analyzes, and exports nearly one billion geo-location records per day. The result was a highly scalable architecture, four times more daily data consumption, and a 50% reduction in cloud costs.

Huq

Isambard Poulson

Co-Founder