Case Study: The Home Depot achieves scalable, cost-efficient analytics with Looker and Google Cloud BigQuery

Helping doers get more done through a data-driven approach

The Home Depot, the world’s largest home-improvement chain, was struggling to scale its on-premises data warehouse as analytics demand grew, data use cases became more complex, and capacity refreshes caused planning headaches and even service outages. To better support its expanding teams, online commerce, AI initiatives, and security needs, the company turned to Looker-related Google Cloud analytics capabilities, including BigQuery.

The solution implemented by Looker/Google Cloud centered on BigQuery, a scalable serverless data warehouse that improved cost control, infrastructure agility, and performance. The Home Depot expanded from 450 terabytes to more than 15 petabytes of data, added capacity without service interruptions, and gained more predictable flat-rate billing. It also improved access control across teams and achieved faster analytics workloads, with specific jobs running significantly faster than on-premises warehousing.

The Home Depot